1.
Greek language
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Greek is an independent branch of the Indo-European family of languages, native to Greece and other parts of the Eastern Mediterranean. It has the longest documented history of any living language, spanning 34 centuries of written records and its writing system has been the Greek alphabet for the major part of its history, other systems, such as Linear B and the Cypriot syllabary, were used previously. The alphabet arose from the Phoenician script and was in turn the basis of the Latin, Cyrillic, Armenian, Coptic, Gothic and many other writing systems. Together with the Latin texts and traditions of the Roman world, during antiquity, Greek was a widely spoken lingua franca in the Mediterranean world and many places beyond. It would eventually become the official parlance of the Byzantine Empire, the language is spoken by at least 13.2 million people today in Greece, Cyprus, Italy, Albania, Turkey, and the Greek diaspora. Greek roots are used to coin new words for other languages, Greek. Greek has been spoken in the Balkan peninsula since around the 3rd millennium BC, the earliest written evidence is a Linear B clay tablet found in Messenia that dates to between 1450 and 1350 BC, making Greek the worlds oldest recorded living language. Among the Indo-European languages, its date of earliest written attestation is matched only by the now extinct Anatolian languages, the Greek language is conventionally divided into the following periods, Proto-Greek, the unrecorded but assumed last ancestor of all known varieties of Greek. The unity of Proto-Greek would have ended as Hellenic migrants entered the Greek peninsula sometime in the Neolithic era or the Bronze Age, Mycenaean Greek, the language of the Mycenaean civilisation. It is recorded in the Linear B script on tablets dating from the 15th century BC onwards, Ancient Greek, in its various dialects, the language of the Archaic and Classical periods of the ancient Greek civilisation. It was widely known throughout the Roman Empire, after the Roman conquest of Greece, an unofficial bilingualism of Greek and Latin was established in the city of Rome and Koine Greek became a first or second language in the Roman Empire. The origin of Christianity can also be traced through Koine Greek, Medieval Greek, also known as Byzantine Greek, the continuation of Koine Greek in Byzantine Greece, up to the demise of the Byzantine Empire in the 15th century. Much of the written Greek that was used as the language of the Byzantine Empire was an eclectic middle-ground variety based on the tradition of written Koine. Modern Greek, Stemming from Medieval Greek, Modern Greek usages can be traced in the Byzantine period and it is the language used by the modern Greeks, and, apart from Standard Modern Greek, there are several dialects of it. In the modern era, the Greek language entered a state of diglossia, the historical unity and continuing identity between the various stages of the Greek language is often emphasised. Greek speakers today still tend to regard literary works of ancient Greek as part of their own rather than a foreign language and it is also often stated that the historical changes have been relatively slight compared with some other languages. According to one estimation, Homeric Greek is probably closer to demotic than 12-century Middle English is to modern spoken English, Greek is spoken by about 13 million people, mainly in Greece, Albania and Cyprus, but also worldwide by the large Greek diaspora. Greek is the language of Greece, where it is spoken by almost the entire population
2.
Cladistics
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Therefore, members of a group are assumed to share a common history and are considered to be closely related. The techniques and nomenclature of cladistics have been applied to other disciplines, Cladistics in the original sense refers to a particular set of methods used in phylogenetic analysis, although it is now sometimes used to refer to the whole field. What is now called the cladistic method appeared as early as 1901 with a work by Peter Chalmers Mitchell for birds and subsequently by Robert John Tillyard in 1921, Hennig referred to his own approach as phylogenetic systematics. Phenetics was championed at this time by the numerical taxonomists Peter Sneath and Robert Sokal, originally conceived, if only in essence, by Willi Hennig in a book published in 1950, cladistics did not flourish until its translation into English in 1966. Today, cladistics is the most popular method for constructing phylogenies from morphological, unlike phenetics, cladistics is specifically aimed at reconstructing evolutionary histories. The way for computational phylogenetics was paved by phenetics, a set of commonly used from the 1950s to 1980s. Phenetics did not try to reconstruct phylogenetic trees, rather, it tried to build dendrograms from similarity data, the cladistic method interprets each character state transformation implied by the distribution of shared character states among taxa as a potential piece of evidence for grouping. The outcome of an analysis is a cladogram – a tree-shaped diagram that is interpreted to represent the best hypothesis of phylogenetic relationships. Cladists contend that these models are unjustified, every cladogram is based on a particular dataset analyzed with a particular method. Different datasets and different methods, not to mention violations of the mentioned assumptions, only scientific investigation can show which is more likely to be correct. Since the cladograms provide competing accounts of events, at most one of them is correct. Within the primates, all anthropoids are hypothesized to have had a common ancestor all of whose descendants were anthropoids, the prosimians, on the other hand, form a paraphyletic taxon. When two or more taxa that are not nested within each other share a plesiomorphy, it is a symplesiomorphy, symplesiomorphies do not mean that the taxa that exhibit that character state are necessarily closely related. For example, Reptilia is traditionally characterized by being cold-blooded, whereas birds are warm-blooded, an apomorphy or derived state is an innovation. It can thus be used to diagnose a clade – or even to help define a clade name in phylogenetic nomenclature, features that are derived in individual taxa are called autapomorphies. Autapomorphies express nothing about relationships among groups, clades are identified by synapomorphies, for example, the possession of digits that are homologous with those of Homo sapiens is a synapomorphy within the vertebrates. The tetrapods can be singled out as consisting of the first vertebrate with such digits homologous to those of Homo sapiens together with all descendants of this vertebrate and it is therefore inferred to have evolved by convergence or reversal. Both mammals and birds are able to maintain a constant body temperature
3.
Phylogenetic tree
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The taxa joined together in the tree are implied to have descended from a common ancestor. Phylogenetic trees are central to the field of phylogenetics, each node is called a taxonomic unit. Internal nodes are generally called hypothetical taxonomic units, as they cannot be directly observed, Trees are useful in fields of biology such as bioinformatics, systematics, and phylogenetic comparative methods. Unrooted trees illustrate only the relatedness of the nodes and do not require the ancestral root to be known or inferred. The idea of a tree of life arose from ancient notions of a progression from lower to higher forms of life. Charles Darwin also produced one of the first illustrations and crucially popularized the notion of a tree in his seminal book The Origin of Species. Over time, species classification has become static and more dynamic. A rooted phylogenetic tree is a tree with a unique node corresponding to the most recent common ancestor of all the entities at the leaves of the tree. The most common method for rooting trees is the use of an uncontroversial outgroup—close enough to allow inference from trait data or molecular sequencing, unrooted trees illustrate the relatedness of the leaf nodes without making assumptions about ancestry. They do not require the ancestral root to be known or inferred, unrooted trees can always be generated from rooted ones by simply omitting the root. By contrast, inferring the root of an unrooted tree requires some means of identifying ancestry, both rooted and unrooted phylogenetic trees can be either bifurcating or multifurcating, and either labeled or unlabeled. In contrast, a rooted multifurcating tree may have more than two children at some nodes and an unrooted multifurcating tree may have more than three neighbors at some nodes. A labeled tree has specific values assigned to its leaves, while a tree, sometimes called a tree shape. The last distinction is the most biologically relevant, it arises because there are places on an unrooted tree to put the root. For labeled bifurcating trees, there are,2 n −2. for n ≥2 total rooted trees and. 2 n −3. for n ≥3 total unrooted trees, among labeled bifurcating trees, the number of unrooted trees with n leaves is equal to the number of rooted trees with n −1 leaves. A dendrogram is a term for the diagrammatic representation of a phylogenetic tree. A cladogram is a phylogenetic tree formed using cladistic methods and this type of tree only represents a branching pattern, i. e. its branch spans do not represent time or relative amount of character change
4.
Clade
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A clade is a group of organisms that consists of a common ancestor and all its lineal descendants, and represents a single branch on the tree of life. The common ancestor may be an individual, a population, a species, clades are nested, one in another, as each branch in turn splits into smaller branches. These splits reflect evolutionary history as populations diverged and evolved independently, over the last few decades, the cladistic approach has revolutionized biological classification and revealed surprising evolutionary relationships among organisms. Increasingly, taxonomists try to avoid naming taxa that are not clades, the term clade was coined in 1957 by the biologist Julian Huxley to refer to the result of cladogenesis, a concept Huxley borrowed from Bernhard Rensch. Many commonly named groups are clades, for example, rodents or insects, because in each case, their name refers to a common ancestor with all its descendant branches. Rodents, for example, are a branch of mammals that split off after the end of the period when the clade Dinosauria stopped being the dominant terrestrial vertebrates 66 million years ago, the original population and all its descendants are a clade. The rodent clade corresponds to the order Rodentia, and insects to the class Insecta and these clades include smaller clades, such as chipmunk or ant, each of which consists of even smaller clades. The clade rodent is in included in the mammal, vertebrate. The phenomenon of convergent evolution is, however, responsible for cases where there are misleading similarities in the morphology of groups that evolved from different lineages. The publication of Darwins theory of evolution in 1859 gave this view increasing weight, thomas Henry Huxley, an early advocate of evolutionary theory, proposed a revised taxonomy based on clades. For example, he grouped birds with reptiles, based on fossil evidence, german biologist Emil Hans Willi Hennig is considered to be the founder of cladistics. Taxonomists have increasingly worked to make the taxonomic system reflect evolution, when it comes to naming, however, this principle is not always compatible with the traditional rank-based nomenclature. For these and other reasons, phylogenetic nomenclature has been developed, a clade is by definition monophyletic, meaning that it contains one ancestor and all its descendants. The ancestor can be known or unknown, any and all members of a clade can be extant or extinct, the science that tries to reconstruct phylogenetic trees and thus discover clades is called phylogenetics or cladistics, the latter term coined by Ernst Mayr, derived from clade. The results of analyses are tree-shaped diagrams called cladograms, they. Three methods of defining clades are featured in phylogenetic nomenclature, node-, stem-, the relationship between clades can be described in several ways, A clade located within a clade is said to be nested within that clade. In the diagram, the clade, i. e. the apes. Two clades are sisters if they have a common ancestor
5.
Most recent common ancestor
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In biology and genealogy, the most recent common ancestor of any set of organisms is the most recent individual from which all organisms in a group are directly descended. The term is also used reference to the ancestry of groups of genes rather than organisms, the MRCA of a set of individuals can sometimes be determined by referring to an established pedigree. However, in general, it is impossible to identify the exact MRCA of a set of individuals. In organisms using sexual reproduction, the matrilinear MRCA and patrilinear MRCA are the MRCAs of a given population considering only matrilineal and patrilineal descent, the MRCA of a population by definition cannot be older than either its matrilinear or its patrilinear MRCA. In the case of Homo sapiens, the matrilinear and patrilinear MRCA are also known as Mitochondrial Eve, the age of the human MRCA is unknown. It is necessarily younger than the age of both Y-MRCA and mt-MRCA, estimated at around 200,000 years, and it may be as recent as some 3,000 years ago. The Last Universal Common Ancestor is the most recent common ancestor of all current life on Earth, the project of a complete description of the phylogeny of biological species is dubbed the Tree of Life. This involves time estimates of all known speciation events, for example, the concept of the last common ancestor from the perspective of human evolution is described for a popular audience in The Ancestors Tale by Richard Dawkins. Dawkins lists concestors of the lineage in order of increasing age, including hominin, hominine, hominid, hominoid. It is also possible to consider the ancestry of individual genes instead of an organism as a whole, coalescent theory describes a stochastic model of how the ancestry of such genetic markers maps to the history of a population. Unlike organisms, a gene is passed down from a generation of organisms to the next generation either as perfect replicas of itself or as slightly mutated descendant genes. While organisms have ancestry graphs and progeny graphs via sexual reproduction, a gene has a chain of ancestors. An organism produced by sexual cross-fertilization has at least two ancestors, but a gene always has one ancestor per generation, Mitochondrial DNA is nearly immune to sexual mixing, unlike the nuclear DNA whose chromosomes are shuffled and recombined in Mendelian inheritance. Mitochondrial DNA, therefore, can be used to trace matrilineal inheritance and to find the Mitochondrial Eve, likewise, Y chromosome is present as a single sex chromosome in the male individual and is passed on to male descendants without recombination. It can be used to trace patrilineal inheritance and to find the Y-chromosomal Adam, Mitochondrial Eve and Y-chromosomal Adam have been established by researchers using genealogical DNA tests. Mitochondrial Eve is estimated to have lived about 200,000 years ago, the MRCA of humans alive today would, therefore, need to have lived more recently than either. It is more complicated to infer human ancestry via autosomal chromosomes, different types of MRCAs are estimated to have lived at different times in the past. These time to MRCA estimates are also computed differently depending on the type of MRCA being considered, patrilineal and matrilineal MRCAs are traced by single gene markers, thus their TMRCA are computed based on DNA test results and established mutation rates as practiced in genetic genealogy
6.
DNA
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Deoxyribonucleic acid is a molecule that carries the genetic instructions used in the growth, development, functioning and reproduction of all known living organisms and many viruses. DNA and RNA are nucleic acids, alongside proteins, lipids and complex carbohydrates, most DNA molecules consist of two biopolymer strands coiled around each other to form a double helix. The two DNA strands are termed polynucleotides since they are composed of simpler units called nucleotides. Each nucleotide is composed of one of four nitrogen-containing nucleobases—cytosine, guanine, adenine, or thymine —a sugar called deoxyribose, and a phosphate group. The nucleotides are joined to one another in a chain by covalent bonds between the sugar of one nucleotide and the phosphate of the next, resulting in an alternating sugar-phosphate backbone. The nitrogenous bases of the two polynucleotide strands are bound together, according to base pairing rules, with hydrogen bonds to make double-stranded DNA. The total amount of related DNA base pairs on Earth is estimated at 5.0 x 1037, in comparison the total mass of the biosphere has been estimated to be as much as 4 trillion tons of carbon. The DNA backbone is resistant to cleavage, and both strands of the double-stranded structure store the same biological information and this information is replicated as and when the two strands separate. A large part of DNA is non-coding, meaning that these sections do not serve as patterns for protein sequences, the two strands of DNA run in opposite directions to each other and are thus antiparallel. Attached to each sugar is one of four types of nucleobases and it is the sequence of these four nucleobases along the backbone that encodes biological information. RNA strands are created using DNA strands as a template in a process called transcription, under the genetic code, these RNA strands are translated to specify the sequence of amino acids within proteins in a process called translation. Within eukaryotic cells DNA is organized into structures called chromosomes. During cell division these chromosomes are duplicated in the process of DNA replication, eukaryotic organisms store most of their DNA inside the cell nucleus and some of their DNA in organelles, such as mitochondria or chloroplasts. In contrast prokaryotes store their DNA only in the cytoplasm, within the eukaryotic chromosomes, chromatin proteins such as histones compact and organize DNA. These compact structures guide the interactions between DNA and other proteins, helping control which parts of the DNA are transcribed, DNA was first isolated by Friedrich Miescher in 1869. DNA is used by researchers as a tool to explore physical laws and theories, such as the ergodic theorem. The unique material properties of DNA have made it an attractive molecule for material scientists and engineers interested in micro-, among notable advances in this field are DNA origami and DNA-based hybrid materials. DNA is a polymer made from repeating units called nucleotides
7.
RNA
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Ribonucleic acid is a polymeric molecule essential in various biological roles in coding, decoding, regulation, and expression of genes. RNA and DNA are nucleic acids, and, along with proteins and carbohydrates, like DNA, RNA is assembled as a chain of nucleotides, but unlike DNA it is more often found in nature as a single-strand folded onto itself, rather than a paired double-strand. Cellular organisms use messenger RNA to convey information that directs synthesis of specific proteins. Many viruses encode their genetic information using an RNA genome, some RNA molecules play an active role within cells by catalyzing biological reactions, controlling gene expression, or sensing and communicating responses to cellular signals. One of these processes is protein synthesis, a universal function where RNA molecules direct the assembly of proteins on ribosomes. This process uses transfer RNA molecules to deliver amino acids to the ribosome, analysis of these RNAs has revealed that they are highly structured. Unlike DNA, their structures do not consist of long double helices, in this fashion, RNAs can achieve chemical catalysis. For instance, determination of the structure of the enzyme that catalyzes peptide bond formation—revealed that its active site is composed entirely of RNA. Each nucleotide in RNA contains a sugar, with carbons numbered 1 through 5. A base is attached to the 1 position, in general, adenine, cytosine, guanine, adenine and guanine are purines, cytosine and uracil are pyrimidines. A phosphate group is attached to the 3 position of one ribose, the phosphate groups have a negative charge each, making RNA a charged molecule. The bases form hydrogen bonds between cytosine and guanine, between adenine and uracil and between guanine and uracil, however, other interactions are possible, such as a group of adenine bases binding to each other in a bulge, or the GNRA tetraloop that has a guanine–adenine base-pair. An important structural feature of RNA that distinguishes it from DNA is the presence of a group at the 2 position of the ribose sugar. The A-form geometry results in a deep and narrow major groove. RNA is transcribed with only four bases, but these bases, pseudouridine, in which the linkage between uracil and ribose is changed from a C–N bond to a C–C bond, and ribothymidine are found in various places. Another notable modified base is hypoxanthine, a deaminated adenine base whose nucleoside is called inosine, inosine plays a key role in the wobble hypothesis of the genetic code. The specific roles of many of these modifications in RNA are not fully understood, the functional form of single-stranded RNA molecules, just like proteins, frequently requires a specific tertiary structure. The scaffold for this structure is provided by secondary structural elements that are hydrogen bonds within the molecule and this leads to several recognizable domains of secondary structure like hairpin loops, bulges, and internal loops
8.
Computational phylogenetics
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Computational phylogenetics is the application of computational algorithms, methods, and programs to phylogenetic analyses. The goal is to assemble a phylogenetic tree representing a hypothesis about the ancestry of a set of genes, species. For example, these techniques have been used to explore the family tree of hominid species, the phylogenetic trees constructed by computational methods are unlikely to perfectly reproduce the evolutionary tree that represents the historical relationships between the species being analyzed. The historical species tree may differ from the historical tree of an individual homologous gene shared by those species. Producing a phylogenetic tree requires a measure of homology among the characteristics shared by the taxa being compared, in morphological studies, this requires explicit decisions about which physical characteristics to measure and how to use them to encode distinct states corresponding to the input taxa. In molecular studies, a problem is in producing a multiple sequence alignment between the genes or amino acid sequences of interest. Progressive sequence alignment methods produce a tree by necessity because they incorporate new sequences into the calculated alignment in order of genetic distance. Phylogenetic trees generated by computational phylogenetics can be rooted or unrooted depending on the input data. A rooted tree is a graph that explicitly identifies a most recent common ancestor. Genetic distance measures can be used to plot a tree with the sequences as leaf nodes. Identification of a root usually requires the inclusion in the data of at least one outgroup known to be only distantly related to the sequences of interest. By contrast, unrooted trees plot the distances and relationships between input sequences without making assumptions regarding their descent. Of course, since not every possible phenotypic characteristic could be measured and encoded for analysis, the decision of which traits to use as a basis for the matrix necessarily represents a hypothesis about which traits of a species or higher taxon are evolutionarily relevant. Morphological studies can be confounded by examples of convergent evolution of phenotypes, a major challenge in constructing useful classes is the high likelihood of inter-taxon overlap in the distribution of the phenotypes variation. However, the most appropriate representation of continuously varying phenotypic measurements is a problem without a general solution. A common method is simply to sort the measurements of interest into two or more classes, rendering continuous observed variation as discretely classifiable, however, defining homology can be challenging due to the inherent difficulties of multiple sequence alignment. For example, given only a pairwise alignment with a gap region, the problem is magnified in MSAs with unaligned and nonoverlapping gaps. In practice, sizable regions of a calculated alignment may be discounted in phylogenetic tree construction to avoid integrating noisy data into the tree calculation
9.
DNA sequencing
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DNA sequencing is the process of determining the precise order of nucleotides within a DNA molecule. It includes any method or technology that is used to determine the order of the four bases—adenine, guanine, cytosine, the advent of rapid DNA sequencing methods has greatly accelerated biological and medical research and discovery. The first DNA sequences were obtained in the early 1970s by academic researchers using laborious methods based on two-dimensional chromatography, following the development of fluorescence-based sequencing methods with a DNA sequencer, DNA sequencing has become easier and orders of magnitude faster. DNA sequencing may be used to determine the sequence of genes, larger genetic regions, full chromosomes or entire genomes. DNA sequencing is also the most efficient way to sequence RNA or proteins, in fact, DNA sequencing has become a key technology in many areas of biology and other sciences such as medicine, forensics, or anthropology. Sequencing is used in biology to study genomes and the proteins they encode. Information obtained using sequencing allows researchers to identify changes in genes, associations with diseases and phenotypes, the field of metagenomics involves identification of organisms present in a body of water, sewage, dirt, debris filtered from the air, or swab samples from organisms. Knowing which organisms are present in an environment is critical to research in ecology, epidemiology, microbiology. Sequencing enables researchers to determine which types of microbes may be present in a microbiome, medical technicians may sequence genes from patients to determine if there is risk of genetic diseases. This is a form of testing, though some genetic tests may not involve DNA sequencing. DNA sequencing may be used along with DNA profiling methods for forensic identification, the canonical structure of DNA has four bases, thymine, adenine, cytosine, and guanine. DNA sequencing is the determination of the order of these bases in a molecule of DNA. However, there are other bases that may be present in a molecule. In some viruses, cytosine may be replaced by hydroxy methyl or hydroxy methyl glucose cytosine, in mammalian DNA, variant bases with methyl groups or phosphosulfate may be found. Depending on the technique, a particular modification, e. g. the 5mC common in humans. This situation changed after 1944 as a result of experiments by Oswald Avery, Colin MacLeod. This was the first time that DNA was shown capable of transforming the properties of cells, in 1953, James Watson and Francis Crick put forward their double-helix model of DNA, based on crystallized X-ray structures being studied by Rosalind Franklin. According to the model, DNA is composed of two strands of nucleotides coiled around each other, linked together by bonds and running in opposite directions
10.
Maximum likelihood estimation
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The method of maximum likelihood corresponds to many well-known estimation methods in statistics. For example, one may be interested in the heights of adult female penguins, MLE would accomplish this by taking the mean and variance as parameters and finding particular parametric values that make the observed results the most probable given the model. In general, for a set of data and underlying statistical model. Maximum likelihood estimation gives a unified approach to estimation, which is well-defined in the case of the normal distribution, maximum-likelihood estimation was recommended, analyzed and widely popularized by Ronald Fisher between 1912 and 1922. Maximum-likelihood estimation finally transcended heuristic justification in a proof published by Samuel S. Wilks in 1938, ironically, the only difficult part of the proof depends on the expected value of the Fisher information matrix, which is provided by a theorem by Fisher. Wilks continued to improve on the generality of the theorem throughout his life, some of the theory behind maximum likelihood estimation was developed for Bayesian statistics. Reviews of the development of maximum likelihood estimation have been provided by a number of authors, suppose there is a sample x1, x2, …, xn of n independent and identically distributed observations, coming from a distribution with an unknown probability density function f0. It is however surmised that the function f0 belongs to a family of distributions, called the parametric model. The value θ0 is unknown and is referred to as the value of the parameter vector. It is desirable to find an estimator θ ^ which would be as close to the true value θ0 as possible, either or both the observed variables xi and the parameter θ can be vectors. To use the method of maximum likelihood, one first specifies the joint density function for all observations, for an independent and identically distributed sample, this joint density function is f = f × f × ⋯ × f. Note that, denotes a separation between the two categories of arguments, the parameters θ and the observations x 1, …, x n. The hat over ℓ indicates that it is akin to some estimator, indeed, ℓ ^ estimates the expected log-likelihood of a single observation in the model. The method of maximum likelihood estimates θ0 by finding a value of θ that maximizes ℓ ^ and this method of estimation defines a maximum likelihood estimator of θ0, ⊆, if a maximum exists. An MLE estimate is the same regardless of whether we maximize the likelihood or the log-likelihood function, for many models, a maximum likelihood estimator can be found as an explicit function of the observed data x1. For many other models, however, no solution to the maximization problem is known or available. For some problems, there may be multiple estimates that maximize the likelihood, in the exposition above, it is assumed that the data are independent and identically distributed. In a simpler extension, an allowance can be made for data heterogeneity, put another way, we are now assuming that each observation xi comes from a random variable that has its own distribution function fi
11.
Mutation
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In biology, a mutation is the permanent alteration of the nucleotide sequence of the genome of an organism, virus, or extrachromosomal DNA or other genetic elements. Mutations may also result from insertion or deletion of segments of DNA due to mobile genetic elements, mutations may or may not produce discernible changes in the observable characteristics of an organism. Mutations play a part in normal and abnormal biological processes including, evolution, cancer, and the development of the immune system. The genomes of RNA viruses are based on RNA rather than DNA, the RNA viral genome can be double stranded or single stranded. In some of these viruses replication occurs quickly and there are no mechanisms to check the genome for accuracy and this error-prone process often results in mutations. Mutation can result in different types of change in sequences. Mutations in genes can either have no effect, alter the product of a gene, mutations can also occur in nongenic regions. Mutations can involve the duplication of large sections of DNA, usually through genetic recombination and these duplications are a major source of raw material for evolving new genes, with tens to hundreds of genes duplicated in animal genomes every million years. Most genes belong to larger families of shared ancestry, known as homology. Here, protein domains act as modules, each with a particular and independent function, that can be mixed together to produce genes encoding new proteins with novel properties. For example, the eye uses four genes to make structures that sense light. Another advantage of duplicating a gene is that this increases engineering redundancy, other types of mutation occasionally create new genes from previously noncoding DNA. Changes in chromosome number may involve even larger mutations, where segments of the DNA within chromosomes break and then rearrange. For example, in the Homininae, two fused to produce human chromosome 2, this fusion did not occur in the lineage of the other apes. Sequences of DNA that can move about the genome, such as transposons, make up a fraction of the genetic material of plants and animals. For example, more than a million copies of the Alu sequence are present in the genome. Another effect of these mobile DNA sequences is that when they move within a genome, they can mutate or delete existing genes, nonlethal mutations accumulate within the gene pool and increase the amount of genetic variation. The abundance of some changes within the gene pool can be reduced by natural selection, while other more favorable mutations may accumulate
12.
Genome
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In modern molecular biology and genetics, a genome is the genetic material of an organism. The genome includes both the genes, the noncoding DNA and the material of the mitochondria and chloroplasts. The term genome was created in 1920 by Hans Winkler, professor of botany at the University of Hamburg, the Oxford Dictionary suggests the name is a blend of the words gene and chromosome. However, see omics for a thorough discussion. A few related -ome words already existed—such as biome, rhizome, Some organisms have multiple copies of chromosomes, diploid, triploid, tetraploid and so on. In classical genetics, in a sexually reproducing organism the gamete has half the number of chromosomes of the somatic cell, the halving of the genetic material in gametes is accomplished by the segregation of homologous chromosomes during meiosis. Additionally, the genome can comprise non-chromosomal genetic elements such as viruses, plasmids, even in species that exist in only one sex, what is described as a genome sequence may be a composite read from the chromosomes of various individuals. Colloquially, the genetic makeup is sometimes used to signify the genome of a particular individual or organism. Both the number of pairs and the number of genes vary widely from one species to another. The only exception in humans is found in red blood cells which become enucleated during development. In 1976, Walter Fiers at the University of Ghent was the first to establish the complete sequence of a viral RNA-genome. The next year Fred Sanger completed the first DNA-genome sequence, Phage Φ-X174, the first genome sequence for an archaeon, Methanococcus jannaschii, was completed in 1996, again by The Institute for Genomic Research. The development of new technologies has made it easier and cheaper to do sequencing. The US National Institutes of Health maintains one of several databases of genomic information. Among the thousands of completed genome sequencing projects include those for rice, a mouse, the plant Arabidopsis thaliana, the fish. In December 2013, scientists first sequenced the genome of a Neanderthal. The genome was extracted from the toe bone of a 130, new sequencing technologies, such as massive parallel sequencing have also opened up the prospect of personal genome sequencing as a diagnostic tool, as pioneered by Manteia Predictive Medicine. A major step toward that goal was the completion in 2007 of the genome of James D. Watson
13.
Synapomorphy
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In phylogenetics, apomorphy and synapomorphy refer to derived characteristic of a clade. Apomorphy implies a characteristic that is different from the form of an ancestor, i. e. an innovation, synapomorphy is a shared derived character or trait state that distinguishes a clade from other organisms. In other words, it is an apomorphy shared by members of a monophyletic group, and thus assumed to be present in their most recent common ancestor. The word synapomorphy, coined by German entomologist Willi Hennig, is derived from the Greek words σύν, syn = shared, ἀπό, apo = away from, a derived character is a character that is derived from an ancestral character over evolutionary history. Derived characters are used in determining phylogenetic relationships, the concept of synapomorphy is relative to a given clade in the tree of life. What counts as a synapomorphy for one clade may well be a character or plesiomorphy at a less inclusive or nested clade. For example, the presence of mammary glands is a synapomorphy for mammals in relation to tetrapods but is a symplesiomorphy for mammals in relation to one another, rodents and primates, for example
14.
Symplesiomorphy
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In phylogenetics, a plesiomorphy, symplesiomorphy or symplesiomorphic character is an ancestral character or trait state shared by two or more taxa. A plesiomorphy refers to the ancestral state, usually in reference to a derived trait state. A symplesiomorphic trait is shared with other taxa that have an earlier last common ancestor with the taxa under consideration. They are therefore not an indication that the taxa be considered closely related to each other than to the more distant taxa. The term symplesiomorphy was first introduced in 1950 by German entomologist Willi Hennig, the concept of plesiomorphy shows the perils of grouping species together purely on the basis of morphologic or genetic similarity without distinguishing ancestral from derived character states. Since a plesiomorphic character inherited from a common ancestor can appear anywhere in a phylogenetic tree, a famous example is the trait of breathing via gills in bony fish and cartilaginous fish. Their kind of respiration is shared by the fishes because it was present in their common ancestor. But based on this trait, we cannot infer that bony fish are more closely related to sharks
15.
Convergent evolution
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Convergent evolution is the independent evolution of similar features in species of different lineages. Convergent evolution creates analogous structures that have similar form or function but were not present in the last common ancestor of those groups, the cladistic term for the same phenomenon is homoplasy. The recurrent evolution of flight is an example, as flying insects, birds. Functionally similar features that have arisen through convergent evolution are analogous, whereas homologous structures or traits have a common origin, bird, bat and pterosaur wings are analogous structures, but their forelimbs are homologous, sharing an ancestral state despite serving different functions. The opposite of convergence is divergent evolution, where related species evolve different traits, convergent evolution is similar to but different from parallel evolution. Many instances of convergent evolution are known in plants, including the development of C4 photosynthesis, seed dispersal by fleshy fruits adapted to be eaten by animals. In morphology, analogous traits arise when different species live in similar ways and/or a similar environment, when occupying similar ecological niches similar problems can lead to similar solutions. The British anatomist Richard Owen was the first to identify the difference between analogies and homologies. In biochemistry, physical and chemical constraints on mechanisms have caused some active site arrangements such as the triad to evolve independently in separate enzyme superfamilies. In his 1989 book Wonderful Life, Stephen Jay Gould argued that if one could rewind the tape of life the same conditions were encountered again, evolution could take a very different course. In cladistics, a homoplasy is a trait shared by two or more taxa for any other than that they share a common ancestry. Taxa which do share ancestry are part of the same clade, homoplastic traits caused by convergence are therefore, from the point of view of cladistics, confounding factors which could lead to an incorrect analysis. In some cases, it is difficult to tell whether a trait has been lost and then re-evolved convergently, or whether a gene has simply been switched off, such a re-emerged trait is called an atavism. From a mathematical standpoint, a gene has a steadily decreasing probability of retaining potential functionality over time. When two species are similar in a character, evolution is defined as parallel if the ancestors were also similar. When the ancestral forms are unspecified or unknown, or the range of traits considered is not clearly specified, the enzymology of proteases provides some of the clearest examples of convergent evolution. These examples reflect the intrinsic chemical constraints on enzymes, leading evolution to converge on equivalent solutions independently and repeatedly, serine and cysteine proteases use different amino acid functional groups as a nucleophile. In order to activate that nucleophile, they orient an acidic, the chemical and physical constraints on enzyme catalysis have caused identical triad arrangements to evolve independently more than 20 times in different enzyme superfamilies
16.
Bat
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Bats are mammals of the order Chiroptera whose forelimbs form webbed wings, making them the only mammals naturally capable of true and sustained flight. By contrast, other mammals said to fly, such as flying squirrels, gliding possums, Bats do not flap their entire forelimbs, as birds do, but instead flap their spread-out digits, which are very long and covered with a thin membrane or patagium. About 70% of bat species are insectivores, most of the rest are frugivores, or fruit eaters. A few species, such as the bat, feed from animals other than insects, with the vampire bats being hematophagous. Bats are present throughout most of the world, with the exception of cold regions. They perform the vital roles of pollinating flowers and dispersing fruit seeds. Bats are economically important, as they consume insect pests, reducing the need for pesticides, the smallest bat is the Kittis hog-nosed bat, measuring 29–34 mm in length,15 cm across the wings and 2–2.6 g in mass. It is also arguably the smallest extant species of mammal, with the Etruscan shrew being the other contender. The largest species of bat are a few species of Pteropus, the Mexican free-tailed bat is the fastest flying animal in horizontal flight. An older English name for bats is flittermouse, which matches their name in other Germanic languages, middle English had bakke, most likely cognate with Old Swedish natbakka, which may have undergone a shift from -k- to -t- influenced by Latin blatta, moth, nocturnal insect. They were formerly grouped in the superorder Archonta, along with the treeshrews, colugos, genetic studies have now placed bats in the superorder Laurasiatheria, along with carnivorans, pangolins, odd-toed ungulates, even-toed ungulates, and cetaceans. A recent study by Zhang et al. places Chiroptera as a taxon to the clade Perissodactyla. The phylogenetic relationships of the different groups of bats have been the subject of much debate and this hypothesis recognized differences between microbats and megabats and acknowledged that flight has only evolved once in mammals. Most molecular biological evidence supports the view that bats form a single or monophyletic group, in the 1980s, a hypothesis based on morphological evidence was offered that stated the Megachiroptera evolved flight separately from the Microchiroptera. The so-called flying primate hypothesis proposes that, when adaptations to flight are removed, one example is that the brains of megabats show a number of advanced characteristics that link them to primates. Although recent genetic studies support the monophyly of bats, debate continues as to the meaning of available genetic. Genetic evidence indicates that megabats originated during the early Eocene and should be placed within the four lines of microbats. Consequently, two new suborders based on molecular data have been proposed and these two new suborders are strongly supported by statistical tests
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Anatomy
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Anatomy is the branch of biology concerned with the study of the structure of organisms and their parts. Anatomy is inherently tied to embryology, comparative anatomy, evolutionary biology, Human anatomy is one of the basic essential sciences of medicine. The discipline of anatomy is divided into macroscopic and microscopic anatomy, macroscopic anatomy, or gross anatomy, is the examination of an animals body parts using unaided eyesight. Gross anatomy also includes the branch of superficial anatomy, microscopic anatomy involves the use of optical instruments in the study of the tissues of various structures, known as histology, and also in the study of cells. The history of anatomy is characterized by an understanding of the functions of the organs. Anatomy and physiology, which study the structure and function of organisms and their parts, make a pair of related disciplines. Derived from the Greek ἀνατομή anatomē dissection, anatomy is the study of the structure of organisms including their systems, organs. It includes the appearance and position of the parts, the materials from which they are composed, their locations. Anatomy is quite distinct from physiology and biochemistry, which deal respectively with the functions of those parts, the discipline of anatomy can be subdivided into a number of branches including gross or macroscopic anatomy and microscopic anatomy. Gross anatomy is the study of large enough to be seen with the naked eye, and also includes superficial anatomy or surface anatomy. Microscopic anatomy is the study of structures on a scale, including histology. Anatomy can be studied using both invasive and non-invasive methods with the goal of obtaining information about the structure and organization of organs, angiography using X-rays or magnetic resonance angiography are methods to visualize blood vessels. The term anatomy is commonly taken to refer to human anatomy, however, substantially the same structures and tissues are found throughout the rest of the animal kingdom and the term also includes the anatomy of other animals. The term zootomy is also used to specifically refer to animals. The structure and tissues of plants are of a dissimilar nature, the kingdom Animalia or metazoa, contains multicellular organisms that are heterotrophic and motile. Most animals have bodies differentiated into separate tissues and these animals are known as eumetazoans. They have a digestive chamber, with one or two openings, the gametes are produced in multicellular sex organs, and the zygotes include a blastula stage in their embryonic development. Metazoans do not include the sponges, which have undifferentiated cells, unlike plant cells, animal cells have neither a cell wall nor chloroplasts
18.
Algorithm
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In mathematics and computer science, an algorithm is a self-contained sequence of actions to be performed. Algorithms can perform calculation, data processing and automated reasoning tasks, an algorithm is an effective method that can be expressed within a finite amount of space and time and in a well-defined formal language for calculating a function. The transition from one state to the next is not necessarily deterministic, some algorithms, known as randomized algorithms, giving a formal definition of algorithms, corresponding to the intuitive notion, remains a challenging problem. In English, it was first used in about 1230 and then by Chaucer in 1391, English adopted the French term, but it wasnt until the late 19th century that algorithm took on the meaning that it has in modern English. Another early use of the word is from 1240, in a manual titled Carmen de Algorismo composed by Alexandre de Villedieu and it begins thus, Haec algorismus ars praesens dicitur, in qua / Talibus Indorum fruimur bis quinque figuris. Which translates as, Algorism is the art by which at present we use those Indian figures, the poem is a few hundred lines long and summarizes the art of calculating with the new style of Indian dice, or Talibus Indorum, or Hindu numerals. An informal definition could be a set of rules that precisely defines a sequence of operations, which would include all computer programs, including programs that do not perform numeric calculations. Generally, a program is only an algorithm if it stops eventually, but humans can do something equally useful, in the case of certain enumerably infinite sets, They can give explicit instructions for determining the nth member of the set, for arbitrary finite n. An enumerably infinite set is one whose elements can be put into one-to-one correspondence with the integers, the concept of algorithm is also used to define the notion of decidability. That notion is central for explaining how formal systems come into being starting from a set of axioms. In logic, the time that an algorithm requires to complete cannot be measured, from such uncertainties, that characterize ongoing work, stems the unavailability of a definition of algorithm that suits both concrete and abstract usage of the term. Algorithms are essential to the way computers process data, thus, an algorithm can be considered to be any sequence of operations that can be simulated by a Turing-complete system. Although this may seem extreme, the arguments, in its favor are hard to refute. Gurevich. Turings informal argument in favor of his thesis justifies a stronger thesis, according to Savage, an algorithm is a computational process defined by a Turing machine. Typically, when an algorithm is associated with processing information, data can be read from a source, written to an output device. Stored data are regarded as part of the state of the entity performing the algorithm. In practice, the state is stored in one or more data structures, for some such computational process, the algorithm must be rigorously defined, specified in the way it applies in all possible circumstances that could arise. That is, any conditional steps must be dealt with, case-by-case
19.
Metric (mathematics)
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In mathematics, a metric or distance function is a function that defines a distance between each pair of elements of a set. A set with a metric is called a metric space, a metric induces a topology on a set, but not all topologies can be generated by a metric. A topological space whose topology can be described by a metric is called metrizable, an important source of metrics in differential geometry are metric tensors, bilinear forms that may be defined from the tangent vectors of a differentiable manifold onto a scalar. A metric tensor allows distances along curves to be determined through integration, however, not every metric comes from a metric tensor in this way. The first condition is implied by the others, for sets on which an addition +, X × X → X is defined, d is called a translation invariant metric if d = d for all x, y and a in X. These conditions express intuitive notions about the concept of distance, for example, that the distance between distinct points is positive and the distance from x to y is the same as the distance from y to x. The triangle inequality means that the distance x to z via y is at least as great as from x to z directly. Euclid in his work stated that the shortest distance between two points is a line, that was the triangle inequality for his geometry, if a modification of the triangle inequality 4*. D ≤ d + d is used in the definition then property 1 follows straight from property 4*, properties 2 and 4* give property 3 which in turn gives property 4. The discrete metric, if x = y then d =0, the Euclidean metric is translation and rotation invariant. The taxicab metric is translation invariant, more generally, any metric induced by a norm is translation invariant. If n ∈ N is a sequence of seminorms defining a vector space E. Graph metric, a defined in terms of distances in a certain graph. The Hamming distance in coding theory, Riemannian metric, a type of metric function that is appropriate to impose on any differentiable manifold. For any such manifold, one chooses at each point p a symmetric, positive definite, bilinear form L, Tp × Tp → ℝ on the tangent space Tp at p, a smooth manifold equipped with a Riemannian metric is called a Riemannian manifold. The Fubini–Study metric on complex projective space and this is an example of a Riemannian metric. String metrics, such as Levenshtein distance and other string edit distances, graph edit distance defines a distance function between graphs. For a given set X, two metrics d1 and d2 are called equivalent if the identity mapping id, → is a homeomorphism
20.
Mathematical optimization
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In mathematics, computer science and operations research, mathematical optimization, also spelled mathematical optimisation, is the selection of a best element from some set of available alternatives. The generalization of optimization theory and techniques to other formulations comprises an area of applied mathematics. Such a formulation is called a problem or a mathematical programming problem. Many real-world and theoretical problems may be modeled in this general framework, typically, A is some subset of the Euclidean space Rn, often specified by a set of constraints, equalities or inequalities that the members of A have to satisfy. The domain A of f is called the space or the choice set. The function f is called, variously, a function, a loss function or cost function, a utility function or fitness function, or, in certain fields. A feasible solution that minimizes the objective function is called an optimal solution, in mathematics, conventional optimization problems are usually stated in terms of minimization. Generally, unless both the function and the feasible region are convex in a minimization problem, there may be several local minima. While a local minimum is at least as good as any nearby points, a global minimum is at least as good as every feasible point. In a convex problem, if there is a minimum that is interior, it is also the global minimum. Optimization problems are often expressed with special notation, consider the following notation, min x ∈ R This denotes the minimum value of the objective function x 2 +1, when choosing x from the set of real numbers R. The minimum value in case is 1, occurring at x =0. Similarly, the notation max x ∈ R2 x asks for the value of the objective function 2x. In this case, there is no such maximum as the function is unbounded. This represents the value of the argument x in the interval, John Wiley & Sons, Ltd. pp. xxviii+489. (2008 Second ed. in French, Programmation mathématique, Théorie et algorithmes, Editions Tec & Doc, Paris,2008. Nemhauser, G. L. Rinnooy Kan, A. H. G. Todd, handbooks in Operations Research and Management Science. Amsterdam, North-Holland Publishing Co. pp. xiv+709, J. E. Dennis, Jr. and Robert B
21.
Least squares
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The method of least squares is a standard approach in regression analysis to the approximate solution of overdetermined systems, i. e. sets of equations in which there are more equations than unknowns. Least squares means that the overall solution minimizes the sum of the squares of the made in the results of every single equation. The most important application is in data fitting, the best fit in the least-squares sense minimizes the sum of squared residuals. Least squares problems fall into two categories, linear or ordinary least squares and non-linear least squares, depending on whether or not the residuals are linear in all unknowns, the linear least-squares problem occurs in statistical regression analysis, it has a closed-form solution. The non-linear problem is solved by iterative refinement, at each iteration the system is approximated by a linear one. Polynomial least squares describes the variance in a prediction of the dependent variable as a function of the independent variable, when the observations come from an exponential family and mild conditions are satisfied, least-squares estimates and maximum-likelihood estimates are identical. The method of least squares can also be derived as a method of moments estimator, the following discussion is mostly presented in terms of linear functions but the use of least-squares is valid and practical for more general families of functions. Also, by iteratively applying local quadratic approximation to the likelihood, for the topic of approximating a function by a sum of others using an objective function based on squared distances, see least squares. The least-squares method is credited to Carl Friedrich Gauss. The accurate description of the behavior of bodies was the key to enabling ships to sail in open seas. The combination of different observations taken under the same conditions contrary to simply trying ones best to observe, the approach was known as the method of averages. The combination of different observations taken under different conditions, the method came to be known as the method of least absolute deviation. It was notably performed by Roger Joseph Boscovich in his work on the shape of the earth in 1757, the development of a criterion that can be evaluated to determine when the solution with the minimum error has been achieved. Laplace tried to specify a mathematical form of the probability density for the errors and he felt these to be the simplest assumptions he could make, and he had hoped to obtain the arithmetic mean as the best estimate. Instead, his estimator was the posterior median, the first clear and concise exposition of the method of least squares was published by Legendre in 1805. The technique is described as a procedure for fitting linear equations to data. The value of Legendres method of least squares was immediately recognized by leading astronomers, in 1809 Carl Friedrich Gauss published his method of calculating the orbits of celestial bodies. In that work he claimed to have been in possession of the method of least squares since 1795 and this naturally led to a priority dispute with Legendre
22.
Neighbor joining
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In bioinformatics, neighbor joining is a bottom-up clustering method for the creation of phylogenetic trees, created by Naruya Saitou and Masatoshi Nei in 1987. Usually used for trees based on DNA or protein sequence data, neighbor joining takes as input a distance matrix specifying the distance between each pair of taxa. Find the pair of distinct taxa i and j for which Q has its lowest value and these taxa are joined to a newly created node, which is connected to the central node. In the figure at right, f and g are joined to the new node u. Calculate the distance from each of the taxa in the pair to this new node, Calculate the distance from each of the taxa outside of this pair to the new node. Start the algorithm again, replacing the pair of joined neighbors with the new node, based on a distance matrix relating the n taxa, calculate Q as follows, where d is the distance between taxa i and j. The branches joining f and u and g and u, and their lengths, δ and δ are part of the tree which is gradually being created, neighbor joining on a set of n taxa requires n −3 iterations. At each step one has to build and search a Q matrix, initially the Q matrix is size n × n, then the next step it is ×, etc. Implementing this in a straightforward way leads to an algorithm with a complexity of O. Let us assume that we have five taxa and the distance matrix D. This is the smallest value of Q1, so we join elements a and b, First branch length estimation Let u denote the new node. Using equation above, we compute the distance from u to each of the other nodes besides a and b, for concreteness, let us join u and c and call the new node v. However, for clarity, we can calculate the Q3 matrix. For example, going from d to b we have 2 +2 +3 +3 =10, a distance matrix whose distances agree in this way with some tree is said to be additive, a property which is rare in practice. Nonetheless it is important to note that, given an additive distance matrix as input, neighbor joining may be viewed as a greedy algorithm for optimizing a tree according to the balanced minimum evolution criterion. For each topology, BME defines the length to be a particular weighted sum of the distances in the distance matrix. The BME optimal topology is the one which minimizes this tree length, neighbor joining at each step greedily joins that pair of taxa which will give the greatest decrease in the estimated tree length. This procedure is not guaranteed to find the topology which is optimal by the BME criterion, the main virtue of NJ is that it is fast,466 as compared to least squares, maximum parsimony and maximum likelihood methods. This makes it practical for analyzing large data sets and for bootstrapping, neighbor joining has the property that if the input distance matrix is correct, then the output tree will be correct. In practice the distance matrix rarely satisfies this condition, but neighbor joining often constructs the correct tree topology anyway, compared with UPGMA and WPGMA, neighbor joining has the advantage that it does not assume all lineages evolve at the same rate
23.
Occam's razor
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Occams razor is a problem-solving principle attributed to William of Ockham, who was an English Franciscan friar, scholastic philosopher and theologian. The principle can be interpreted as stating Among competing hypotheses, the one with the fewest assumptions should be selected, in science, Occams razor is used as a heuristic technique to guide scientists in the development of theoretical models, rather than as an arbiter between published models. The term Occams razor did not appear until a few centuries after William of Ockhams death in 1347, libert Froidmont, in his On Christian Philosophy of the Soul, takes credit for the phrase, speaking of novacula occami. Ockham did not invent this principle, but the association with him may be due to the frequency. The origins of what has come to be known as Occams razor are traceable to the works of philosophers such as John Duns Scotus, Robert Grosseteste, Maimonides. Aristotle writes in his Posterior Analytics, We may assume the superiority ceteris paribus of the demonstration which derives from fewer postulates or hypotheses, ptolemy stated, We consider it a good principle to explain the phenomena by the simplest hypothesis possible. Phrases such as It is vain to do more what can be done with fewer. Robert Grosseteste, in Commentary on the Posterior Analytics Books, declares, That is better, similarly in natural science, in moral science, and in metaphysics the best is that which needs no premises and the better that which needs the fewer, other circumstances being equal. The Summa Theologica of Thomas Aquinas states that it is superfluous to suppose that what can be accounted for by a few principles has been produced by many. Aquinas uses this principle to construct an objection to Gods existence, an objection that he in turn answers and refutes generally, hence, Aquinas acknowledges the principle that today is known as Occams razor, but prefers causal explanations to other simple explanations. The Indian Hindu philosopher Madhva in verse 400 of his Vishnu-Tattva-Nirnaya says, William of Ockham was an English Franciscan friar and theologian, an influential medieval philosopher and a nominalist. His popular fame as a great logician rests chiefly on the maxim attributed to him, the term razor refers to distinguishing between two hypotheses either by shaving away unnecessary assumptions or cutting apart two similar conclusions. This principle is sometimes phrased as pluralitas non est ponenda sine necessitate, in his Summa Totius Logicae, i. 12, Ockham cites the principle of economy, Frustra fit per plura quod potest fieri per pauciora, to quote Isaac Newton, We are to admit no more causes of natural things than such as are both true and sufficient to explain their appearances. Therefore, to the natural effects we must, as far as possible. Bertrand Russell offers a version of Occams razor, Whenever possible. The only assumption is that the environment follows some unknown but computable probability distribution and this theory is a mathematical formalization of Occams razor. Another technical approach to Occams razor is ontological parsimony, the widespread laymans formulation that the simplest explanation is usually the correct one appears to have been derived from Occams razor
24.
Bayesian inference
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Bayesian inference is a method of statistical inference in which Bayes theorem is used to update the probability for a hypothesis as more evidence or information becomes available. Bayesian inference is an important technique in statistics, and especially in mathematical statistics, Bayesian updating is particularly important in the dynamic analysis of a sequence of data. Bayesian inference has found application in a range of activities, including science, engineering, philosophy, medicine, sport. In the philosophy of theory, Bayesian inference is closely related to subjective probability. Bayesian inference derives the probability as a consequence of two antecedents, a prior probability and a likelihood function derived from a statistical model for the observed data. Bayesian inference computes the probability according to Bayes theorem, P = P ⋅ P P where ∣ means event conditional on. H stands for any hypothesis whose probability may be affected by data, often there are competing hypotheses, and the task is to determine which is the most probable. The evidence E corresponds to new data that were not used in computing the prior probability, P, the prior probability, is the estimate of the probability of the hypothesis H before the data E, the current evidence, is observed. P, the probability, is the probability of H given E, i. e. after E is observed. This is what we want to know, the probability of a hypothesis given the observed evidence, P is the probability of observing E given H. As a function of E with H fixed, this is the likelihood – it indicates the compatibility of the evidence with the given hypothesis. The likelihood function is a function of the evidence, E, while the probability is a function of the hypothesis. This factor is the same for all possible hypotheses being considered, Bayes rule can also be written as follows, P = P P ⋅ P where the factor P P can be interpreted as the impact of E on the probability of H. If the evidence does not match up with a hypothesis, one should reject the hypothesis, but if a hypothesis is extremely unlikely a priori, one should also reject it, even if the evidence does appear to match up. The critical point about Bayesian inference, then, is that it provides a way of combining new evidence with prior beliefs. This allows for Bayesian principles to be applied to various kinds of evidence and this procedure is termed Bayesian updating. Bayesian updating is widely used and computationally convenient, however, it is not the only updating rule that might be considered rational. Ian Hacking noted that traditional Dutch book arguments did not specify Bayesian updating, Hacking wrote And neither the Dutch book argument, nor any other in the personalist arsenal of proofs of the probability axioms, entails the dynamic assumption
25.
Maximum parsimony (phylogenetics)
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In phylogenetics, maximum parsimony is an optimality criterion under which the phylogenetic tree that minimizes the total number of character-state changes is to be preferred. Under the maximum-parsimony criterion, the tree will minimize the amount of homoplasy. In other words, under criterion, the shortest possible tree that explains the data is considered best. The principle is akin to Occams razor, which states that—all else being equal—the simplest hypothesis that explains the data should be selected, some of the basic ideas behind maximum parsimony were presented by James S. Farris in 1970 and Walter M. Fitch in 1971. Maximum parsimony is an intuitive and simple criterion, and it is popular for this reason, however, although it is easy to score a phylogenetic tree, there is no algorithm to quickly generate the most-parsimonious tree. Instead, the tree must be found in tree space. For a small number of taxa it is possible to do a search, in which every possible tree is scored. For nine to twenty taxa, it will generally be preferable to use branch-and-bound, for greater numbers of taxa, a heuristic search must be performed. In addition, maximum parsimony is not statistically consistent and that is, it is not guaranteed to produce the true tree with high probability, given sufficient data. As demonstrated in 1978 by Joe Felsenstein, maximum parsimony can be inconsistent under certain conditions, the maximization of parsimony has proven useful in many fields. Occams razor, a principle of theoretical parsimony suggested by William of Ockham in the 1320s, while evolution is not an inherently parsimonious process, centuries of scientific experience lend support to the aforementioned principle of parsimony. Namely, the supposition of a simpler, more parsimonious chain of events is preferable to the supposition of a more complicated, hence, parsimony is typically sought in constructing phylogenetic trees, and in scientific explanation generally. Maximum parsimony is used with most kinds of data, until recently. Estimating phylogenies is not a trivial problem, a huge number of possible phylogenetic trees exist for any reasonably sized set of taxa, for example, a mere ten species gives over two million possible unrooted trees. These possibilities must be searched to find a tree that best fits the data according to the optimality criterion, however, the data themselves do not lead to a simple, arithmetic solution to the problem. Ideally, we would expect the distribution of whatever evolutionary characters to follow the branching pattern of evolution. Thus we could say if two organisms possess a shared character, they should be more closely related to each other than to a third organism that lacks this character. We would predict that bats and monkeys are more related to each other than either is to an elephant, because male bats and monkeys possess external testicles
26.
Simulated annealing
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Simulated annealing is a probabilistic technique for approximating the global optimum of a given function. Specifically, it is a metaheuristic to approximate global optimization in a search space. It is often used when the space is discrete. The name and inspiration come from annealing in metallurgy, a technique involving heating and controlled cooling of a material to increase the size of its crystals, both are attributes of the material that depend on its thermodynamic free energy. Heating and cooling the material both the temperature and the thermodynamic free energy. Khachaturyan, Svetlana V. Semenovskaya, Boris K. Vainshtein in 1979 and by Armen G. Khachaturyan, Svetlana V. Semenovskaya and these authors used computer simulation mimicking annealing and cooling of such a system to find its global minimum. This notion of slow cooling implemented in the Simulated Annealing algorithm is interpreted as a decrease in the probability of accepting worse solutions as the solution space is explored. The method is an adaptation of the Metropolis–Hastings algorithm, a Monte Carlo method to sample states of a thermodynamic system. Rosenbluth and published by N. Metropolis et al. in 1953, the state of some physical systems, and the function E to be minimized is analogous to the internal energy of the system in that state. The goal is to bring the system, from an initial state. At each step, the SA heuristic considers some neighbouring state s of the current state s and these probabilities ultimately lead the system to move to states of lower energy. Typically this step is repeated until the system reaches a state that is enough for the application. Optimization of a solution involves evaluating the neighbours of a state of the problem, the well-defined way in which the states are altered to produce neighbouring states is called a move, and different moves give different sets of neighbouring states. These moves usually result in alterations of the last state. States with a smaller energy are better than those with a greater energy, the probability function P must be positive even when e ′ is greater than e. This feature prevents the method from becoming stuck at a minimum that is worse than the global one. When T tends to zero, the probability P must tend to zero if e ′ > e, for sufficiently small values of T, the system will then increasingly favor moves that go downhill, and avoid those that go uphill. With T =0 the procedure reduces to the greedy algorithm, which makes only the downhill transitions
27.
Basal (phylogenetics)
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In phylogenetics, basal is the direction of the base of a rooted phylogenetic tree or cladogram. Clade C may be described as basal within a larger clade D if its root is linked to the root of D. If C is a clade within D that has the lowest taxonomic rank of all basal clades within D, C may be described as the basal taxon of that rank within D. While there must always be two or more equally basal clades sprouting from the root of every cladogram, those clades may differ widely in rank or species diversity. In general, clade A is more basal than clade B if B is a subgroup of the group of A. Within large groups, basal may be used loosely to mean closer to the root than the great majority of. A core clade is a clade representing all but the clade of lowest rank within a larger clade. While basal applies to clades, characters or traits are considered derived if they are absent in a basal group. This assumption only holds if the basal group is a good analogy for the last common ancestor of the group. Ancestral or plesiomorphic are preferred to primitive, which may carry false connotations of inferiority or a lack of complexity, within the primate family Hominidae, gorillas are a sister group to common chimpanzees, bonobos and humans. These five species form a clade, the subfamily Homininae, of which Gorilla is the basal genus, however, if the analysis is not restricted to genera, the Homo plus Pan clade is also basal. This semantic ambiguity is discussed in the Criticism section, moreover, orangutans are a sister group to Homininae and are the basal genus in the family as a whole. Subfamilies Homininae and Ponginae are both basal within Hominidae, but given that there are no subfamilies in the cladogram it is unlikely the term would be applied to either. In general, a statement to the effect that one group is basal, or branches off first, if that level cannot be specified a more detailed description of the relevant sister groups may be needed. In this example, orangutans differ from the genera in their Eurasian range. This fact plus their basal status provides a hint that the most recent common ancestor of extant great apes may have been Eurasian, despite the ubiquity of the usage of the term, some systematists believe its application to extant groups is unnecessary and misleading. This is because a pair of branches of a phylogenetic tree are equally ranked. The term tends to be applied when one branch is less diverse than another branch and this situation raises an equivocal usage for the term basal in that it also refers to the direction of the root of the tree
28.
Phylogenetics
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In biology, phylogenetics /ˌfaɪloʊdʒəˈnɛtɪks, -lə-/ is the study of the evolutionary history and relationships among individuals or groups of organisms. These relationships are discovered through phylogenetic inference methods that evaluate observed heritable traits, the result of these analyses is a phylogeny – a diagrammatic hypothesis about the history of the evolutionary relationships of a group of organisms. The tips of a tree can be living organisms or fossils. Phylogenetic analyses have become central to understanding biodiversity, evolution, ecology, taxonomy is the classification, identification and naming of organisms. It is usually richly informed by phylogenetics, but remains a methodologically and logically distinct discipline, usual methods of phylogenetic inference involve computational approaches implementing the optimality criteria and methods of parsimony, maximum likelihood, and MCMC-based Bayesian inference. All these depend upon an implicit or explicit mathematical model describing the evolution of characters observed, prior to 1990, phylogenetic inferences were generally presented as narrative scenarios. Such methods are often ambiguous and lack explicit criteria for evaluating alternative hypotheses, the term phylogeny derives from the German Phylogenie, introduced by Haeckel in 1866, and the Darwinian approach to classification became known as the phyletic approach. During the late 19th century, Ernst Haeckels recapitulation theory, or biogenetic fundamental law, was widely accepted, but this theory has long been rejected. O. See, Huerta-Cepas, Jaime, Dopazo, Joaquín, Gabaldón, ETE, A python Environment for Tree Exploration. PhylomeDB, A public database hosting thousands of gene phylogenies ranging many different species, See, Huerta-Cepas, J. Capella-Gutierrez, S. Pryszcz, L. P. Denisov, I. Kormes, D. Marcet-Houben, M. Gabaldón, T. PhylomeDB v3.0, An expanding repository of genome-wide collections of trees, alignments, lents, N. H. Cifuentes, O. E. Carpi, A. Teaching the Process of Molecular Phylogeny and Systematics, A Multi-Part Inquiry-Based Exercise
29.
Dendrogram
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A dendrogram is a tree diagram frequently used to illustrate the arrangement of the clusters produced by hierarchical clustering. Dendrograms are often used in biology to illustrate the clustering of genes or samples, sometimes on top of heatmaps. For a clustering example, suppose this data is to be clustered using Euclidean distance as the distance metric, iris dendrogram - Example of using a dendrogram to visualize the 3 clusters from hierarchical clustering using the complete method vs the real species category
30.
JSTOR
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JSTOR is a digital library founded in 1995. Originally containing digitized back issues of journals, it now also includes books and primary sources. It provides full-text searches of almost 2,000 journals, more than 8,000 institutions in more than 160 countries have access to JSTOR, most access is by subscription, but some older public domain content is freely available to anyone. William G. Bowen, president of Princeton University from 1972 to 1988, JSTOR originally was conceived as a solution to one of the problems faced by libraries, especially research and university libraries, due to the increasing number of academic journals in existence. Most libraries found it prohibitively expensive in terms of cost and space to maintain a collection of journals. By digitizing many journal titles, JSTOR allowed libraries to outsource the storage of journals with the confidence that they would remain available long-term, online access and full-text search ability improved access dramatically. Bowen initially considered using CD-ROMs for distribution, JSTOR was initiated in 1995 at seven different library sites, and originally encompassed ten economics and history journals. JSTOR access improved based on feedback from its sites. Special software was put in place to make pictures and graphs clear, with the success of this limited project, Bowen and Kevin Guthrie, then-president of JSTOR, wanted to expand the number of participating journals. They met with representatives of the Royal Society of London and an agreement was made to digitize the Philosophical Transactions of the Royal Society dating from its beginning in 1665, the work of adding these volumes to JSTOR was completed by December 2000. The Andrew W. Mellon Foundation funded JSTOR initially, until January 2009 JSTOR operated as an independent, self-sustaining nonprofit organization with offices in New York City and in Ann Arbor, Michigan. JSTOR content is provided by more than 900 publishers, the database contains more than 1,900 journal titles, in more than 50 disciplines. Each object is identified by an integer value, starting at 1. In addition to the site, the JSTOR labs group operates an open service that allows access to the contents of the archives for the purposes of corpus analysis at its Data for Research service. This site offers a facility with graphical indication of the article coverage. Users may create focused sets of articles and then request a dataset containing word and n-gram frequencies and they are notified when the dataset is ready and may download it in either XML or CSV formats. The service does not offer full-text, although academics may request that from JSTOR, JSTOR Plant Science is available in addition to the main site. The materials on JSTOR Plant Science are contributed through the Global Plants Initiative and are only to JSTOR
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International Standard Book Number
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The International Standard Book Number is a unique numeric commercial book identifier. An ISBN is assigned to each edition and variation of a book, for example, an e-book, a paperback and a hardcover edition of the same book would each have a different ISBN. The ISBN is 13 digits long if assigned on or after 1 January 2007, the method of assigning an ISBN is nation-based and varies from country to country, often depending on how large the publishing industry is within a country. The initial ISBN configuration of recognition was generated in 1967 based upon the 9-digit Standard Book Numbering created in 1966, the 10-digit ISBN format was developed by the International Organization for Standardization and was published in 1970 as international standard ISO2108. Occasionally, a book may appear without a printed ISBN if it is printed privately or the author does not follow the usual ISBN procedure, however, this can be rectified later. Another identifier, the International Standard Serial Number, identifies periodical publications such as magazines, the ISBN configuration of recognition was generated in 1967 in the United Kingdom by David Whitaker and in 1968 in the US by Emery Koltay. The 10-digit ISBN format was developed by the International Organization for Standardization and was published in 1970 as international standard ISO2108, the United Kingdom continued to use the 9-digit SBN code until 1974. The ISO on-line facility only refers back to 1978, an SBN may be converted to an ISBN by prefixing the digit 0. For example, the edition of Mr. J. G. Reeder Returns, published by Hodder in 1965, has SBN340013818 -340 indicating the publisher,01381 their serial number. This can be converted to ISBN 0-340-01381-8, the check digit does not need to be re-calculated, since 1 January 2007, ISBNs have contained 13 digits, a format that is compatible with Bookland European Article Number EAN-13s. An ISBN is assigned to each edition and variation of a book, for example, an ebook, a paperback, and a hardcover edition of the same book would each have a different ISBN. The ISBN is 13 digits long if assigned on or after 1 January 2007, a 13-digit ISBN can be separated into its parts, and when this is done it is customary to separate the parts with hyphens or spaces. Separating the parts of a 10-digit ISBN is also done with either hyphens or spaces, figuring out how to correctly separate a given ISBN number is complicated, because most of the parts do not use a fixed number of digits. ISBN issuance is country-specific, in that ISBNs are issued by the ISBN registration agency that is responsible for country or territory regardless of the publication language. Some ISBN registration agencies are based in national libraries or within ministries of culture, in other cases, the ISBN registration service is provided by organisations such as bibliographic data providers that are not government funded. In Canada, ISBNs are issued at no cost with the purpose of encouraging Canadian culture. In the United Kingdom, United States, and some countries, where the service is provided by non-government-funded organisations. Australia, ISBNs are issued by the library services agency Thorpe-Bowker
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Willi Hennig
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Emil Hans Willi Hennig was a German biologist who is considered the founder of phylogenetic systematics, also known as cladistics. In 1945 as a prisoner of war, Hennig began work on his theory of cladistics, with his works on evolution and systematics he revolutionised the view of the natural order of beings. As a taxonomist, he specialised in dipterans, Hennig was born in Dürrhennersdorf, Upper Lusatia. His mother Marie Emma, née Groß, worked as a maid and, later and his father Karl Ernst Emil Hennig was a rail worker. Willi had two brothers, Fritz Rudolf Hennig, who became a minister, and Karl Herbert, who went missing at Stalingrad in 1943, in the spring of 1919, Willi Hennig started school in Dürrhennersdorf, and subsequently was at school in Taubenheim an der Spree and Oppach. Rudolf Hennig described the family as calm, his father possessed an even temperament, as of 1927, Willi Hennig continued his education at the Realgymnasium and boarding school in Klotzsche near Dresden. Here he met his first mentor M. Rost, a science teacher, Rost had an interest in insects and introduced Hennig to Wilhelm Meise, who worked as a scientist at the Dresdener Museum für Tierkunde. In 1930, Hennig skipped a year, and graduated on February 26,1932, as early as 1931, Willi Hennig composed an essay entitled Die Stellung der Systematik in der Zoologie as part of his school work, published posthumously in 1978. It showed his interest as well as his treatment of systematic problems. From the summer semester of 1932 onwards, Hennig read zoology, botany and he would continue to visit the Museum in Dresden. There, he met the curator of the collection, the Dipteran expert Fritz Isidor van Emden. Hennig saw him regularly until van Emden was expelled from National Socialist Germany for having a Jewish mother, Hennig developed a deep friendship with Emdens successor, Klaus Günther. Hennig concluded his studies with a dissertation entitled, Beiträge zur Kenntnis des Kopulationsapparates der cyclorrhaphen Dipteren, by this time, Hennig had published eight scientific papers. Besides his 300-page revision of the Tylidae, there were papers on Diptera. After his studies, Hennig was Volontär at the State Museum for Zoology in Dresden, on January 1,1937, he obtained a scholarship from the Deutsche Forschungsgemeinschaft to work at the German Entomological Institute of the Kaiser-Wilhelm-Gesellschaft in Berlin-Dahlem. On May 13,1939, Hennig married his fellow student Irma Wehnert. By 1945, they had three sons, Wolfgang, Bernd and Gerd, Willi Hennig was drafted in 1938 to train for the infantry and concluded this course in 1939. As of the start of World War II, he was deployed in the infantry in Poland, France, Denmark and Russia
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PubMed Identifier
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PubMed is a free search engine accessing primarily the MEDLINE database of references and abstracts on life sciences and biomedical topics. The United States National Library of Medicine at the National Institutes of Health maintains the database as part of the Entrez system of information retrieval, from 1971 to 1997, MEDLINE online access to the MEDLARS Online computerized database primarily had been through institutional facilities, such as university libraries. PubMed, first released in January 1996, ushered in the era of private, free, home-, the PubMed system was offered free to the public in June 1997, when MEDLINE searches via the Web were demonstrated, in a ceremony, by Vice President Al Gore. Information about the journals indexed in MEDLINE, and available through PubMed, is found in the NLM Catalog. As of 5 January 2017, PubMed has more than 26.8 million records going back to 1966, selectively to the year 1865, and very selectively to 1809, about 500,000 new records are added each year. As of the date,13.1 million of PubMeds records are listed with their abstracts. In 2016, NLM changed the system so that publishers will be able to directly correct typos. Simple searches on PubMed can be carried out by entering key aspects of a subject into PubMeds search window, when a journal article is indexed, numerous article parameters are extracted and stored as structured information. Such parameters are, Article Type, Secondary identifiers, Language, publication type parameter enables many special features. As these clinical girish can generate small sets of robust studies with considerable precision, since July 2005, the MEDLINE article indexing process extracts important identifiers from the article abstract and puts those in a field called Secondary Identifier. The secondary identifier field is to store numbers to various databases of molecular sequence data, gene expression or chemical compounds. For clinical trials, PubMed extracts trial IDs for the two largest trial registries, ClinicalTrials. gov and the International Standard Randomized Controlled Trial Number Register, a reference which is judged particularly relevant can be marked and related articles can be identified. If relevant, several studies can be selected and related articles to all of them can be generated using the Find related data option, the related articles are then listed in order of relatedness. To create these lists of related articles, PubMed compares words from the title and abstract of each citation, as well as the MeSH headings assigned, using a powerful word-weighted algorithm. The related articles function has been judged to be so precise that some researchers suggest it can be used instead of a full search, a strong feature of PubMed is its ability to automatically link to MeSH terms and subheadings. Examples would be, bad breath links to halitosis, heart attack to myocardial infarction, where appropriate, these MeSH terms are automatically expanded, that is, include more specific terms. Terms like nursing are automatically linked to Nursing or Nursing and this important feature makes PubMed searches automatically more sensitive and avoids false-negative hits by compensating for the diversity of medical terminology. The My NCBI area can be accessed from any computer with web-access, an earlier version of My NCBI was called PubMed Cubby
Media related to Cladograms at Wikimedia Commons
