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Glimmer Twins
In bioinformatics, GLIMMER (Gene Locator and Interpolated Markov ModelER) is used to find genes in prokaryotic DNA. "It is effective at finding genes in bacteria, archea, viruses, typically finding 98-99% of all relatively long protein coding genes". GLIMMER was the first system that used the interpolated Markov model to identify coding regions. The GLIMMER software is open source and is maintained by Steven Salzberg, Art Delcher, and their colleagues at the ''Center for Computational Biology'' at Johns Hopkins University. The original GLIMMER algorithms and software were designed by Art Delcher, Simon Kasif and Steven Salzberg and applied to bacterial genome annotation in collaboration with Owen White. Versions GLIMMER 1.0 First Version of GLIMMER "i.e., GLIMMER 1.0" was released in 1998 and it was published in the paper ''Microbial gene identification using interpolated Markov model''. Markov models were used to identify microbial genes in GLIMMER 1.0. GLIMMER considers the ...
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Bioinformatics
Bioinformatics () is an interdisciplinary field that develops methods and software tools for understanding biological data, in particular when the data sets are large and complex. As an interdisciplinary field of science, bioinformatics combines biology, chemistry, physics, computer science, information engineering, mathematics and statistics to analyze and interpret the biological data. Bioinformatics has been used for '' in silico'' analyses of biological queries using computational and statistical techniques. Bioinformatics includes biological studies that use computer programming as part of their methodology, as well as specific analysis "pipelines" that are repeatedly used, particularly in the field of genomics. Common uses of bioinformatics include the identification of candidates genes and single nucleotide polymorphisms ( SNPs). Often, such identification is made with the aim to better understand the genetic basis of disease, unique adaptations, desirable properties ...
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Minimum Description Length
Minimum Description Length (MDL) is a model selection principle where the shortest description of the data is the best model. MDL methods learn through a data compression perspective and are sometimes described as mathematical applications of Occam's razor. The MDL principle can be extended to other forms of inductive inference and learning, for example to estimation and sequential prediction, without explicitly identifying a single model of the data. MDL has its origins mostly in information theory and has been further developed within the general fields of statistics, theoretical computer science and machine learning, and more narrowly computational learning theory. Historically, there are different, yet interrelated, usages of the definite noun phrase "''the'' minimum description length ''principle''" that vary in what is meant by ''description'': * Within Jorma Rissanen's theory of learning, a central concept of information theory, models are statistical hypotheses and descr ...
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Gibbs Sampling
In statistics, Gibbs sampling or a Gibbs sampler is a Markov chain Monte Carlo (MCMC) algorithm for obtaining a sequence of observations which are approximated from a specified multivariate probability distribution, when direct sampling is difficult. This sequence can be used to approximate the joint distribution (e.g., to generate a histogram of the distribution); to approximate the marginal distribution of one of the variables, or some subset of the variables (for example, the unknown parameters or latent variables); or to compute an integral (such as the expected value of one of the variables). Typically, some of the variables correspond to observations whose values are known, and hence do not need to be sampled. Gibbs sampling is commonly used as a means of statistical inference, especially Bayesian inference. It is a randomized algorithm (i.e. an algorithm that makes use of random numbers), and is an alternative to deterministic algorithms for statistical inferenc ...
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Ribosomal Binding Site
A ribosome binding site, or ribosomal binding site (RBS), is a sequence of nucleotides upstream of the start codon of an mRNA transcript that is responsible for the recruitment of a ribosome during the initiation of translation. Mostly, RBS refers to bacterial sequences, although internal ribosome entry sites (IRES) have been described in mRNAs of eukaryotic cells or viruses that infect eukaryotes. Ribosome recruitment in eukaryotes is generally mediated by the 5' cap present on eukaryotic mRNAs. Prokaryotes The RBS in prokaryotes is a region upstream of the start codon. This region of the mRNA has the consensus 5'-AGGAGG-3', also called the Shine-Dalgarno (SD) sequence. The complementary sequence (CCUCCU), called the anti-Shine-Dalgarno (ASD) is contained in the 3’ end of the 16S region of the smaller (30S) ribosomal subunit. Upon encountering the Shine-Dalgarno sequence, the ASD of the ribosome base pairs with it, after which translation is initiated. Variations of the 5'-AG ...
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Case2
Case or CASE may refer to: Containers * Case (goods), a package of related merchandise * Cartridge case or casing, a firearm cartridge component * Bookcase, a piece of furniture used to store books * Briefcase or attaché case, a narrow box to carry paperwork * Computer case, the enclosure for a PC's main components * Keep case, DVD or CD packaging * Pencil case * Phone case, protective or vanity accessory for mobile phones ** Battery case * Road case or flight case, for fragile equipment in transit * Shipping container or packing case * Suitcase, a large luggage box * Type case, a compartmentalized wooden box for letterpress typesetting Places * Case, Laclede County, Missouri * Case, Warren County, Missouri * Case River, a Kabika tributary in Ontario, Canada * Case Township, Michigan * Case del Conte, Italy People * Case (name), people with the surname (or given name) * Case (singer), American R&B singer-songwriter and producer (Case Woodard) Arts, entertainment, and media ...
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Case 1
Case or CASE may refer to: Containers * Case (goods), a package of related merchandise * Cartridge case or casing, a firearm cartridge component * Bookcase, a piece of furniture used to store books * Briefcase or attaché case, a narrow box to carry paperwork * Computer case, the enclosure for a PC's main components * Keep case, DVD or CD packaging * Pencil case * Phone case, protective or vanity accessory for mobile phones ** Battery case * Road case or flight case, for fragile equipment in transit * Shipping container or packing case * Suitcase, a large luggage box * Type case, a compartmentalized wooden box for letterpress typesetting Places * Case, Laclede County, Missouri * Case, Warren County, Missouri * Case River, a Kabika tributary in Ontario, Canada * Case Township, Michigan * Case del Conte, Italy People * Case (name), people with the surname (or given name) * Case (singer), American R&B singer-songwriter and producer (Case Woodard) Arts, entertainment, and media ...
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Oligomer
In chemistry and biochemistry, an oligomer () is a molecule that consists of a few repeating units which could be derived, actually or conceptually, from smaller molecules, monomers.Quote: ''Oligomer molecule: A molecule of intermediate relative molecular mass, the structure of which essentially comprises a small plurality of units derived, actually or conceptually, from molecules of lower relative molecular mass.'' The name is composed of Greek elements '' oligo-'', "a few" and '' -mer'', "parts". An adjective form is ''oligomeric''. The oligomer concept is contrasted to that of a polymer, which is usually understood to have a large number of units, possibly thousands or millions. However, there is no sharp distinction between these two concepts. One proposed criterion is whether the molecule's properties vary significantly with the removal of one or a few of the units. An oligomer with a specific number of units is referred to by the Greek prefix denoting that number, ...
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K-mer
In bioinformatics, ''k''-mers are substrings of length k contained within a biological sequence. Primarily used within the context of computational genomics and sequence analysis, in which ''k''-mers are composed of nucleotides (''i.e''. A, T, G, and C), ''k''-mers are capitalized upon to assemble DNA sequences, improve heterologous gene expression, identify species in metagenomic samples, and create attenuated vaccines. Usually, the term ''k''-mer refers to all of a sequence's subsequences of length k, such that the sequence AGAT would have four monomers (A, G, A, and T), three 2-mers (AG, GA, AT), two 3-mers (AGA and GAT) and one 4-mer (AGAT). More generally, a sequence of length L will have L - k + 1 ''k''-mers and n^ total possible ''k''-mers, where n is number of possible monomers (e.g. four in the case of DNA). Introduction ''k''-mers are simply length k subsequences. For example, all the possible ''k''-mers of a DNA sequence are shown below: A method of visualizi ...
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Noncoding DNA
Non-coding DNA (ncDNA) sequences are components of an organism's DNA that do not encode protein sequences. Some non-coding DNA is transcribed into functional non-coding RNA molecules (e.g. transfer RNA, microRNA, piRNA, ribosomal RNA, and regulatory RNAs). Other functional regions of the non-coding DNA fraction include regulatory sequences that control gene expression; scaffold attachment regions; origins of DNA replication; centromeres; and telomeres. Some non-coding regions appear to be mostly nonfunctional such as introns, pseudogenes, intergenic DNA, and fragments of transposons and viruses. Fraction of non-coding genomic DNA In bacteria, the coding regions typically take up 88 % of the genome. The remaining 12 % consists largely of non-coding genes and regulatory sequences, which means that almost all of the bacterial genome has a function. The amount of coding DNA in eukaryrotes is usually a much smaller fraction of the genome because eukaryotic genom ...
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Training Set
In machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. Such algorithms function by making data-driven predictions or decisions, through building a mathematical model from input data. These input data used to build the model are usually divided in multiple data sets. In particular, three data sets are commonly used in different stages of the creation of the model: training, validation and test sets. The model is initially fit on a training data set, which is a set of examples used to fit the parameters (e.g. weights of connections between neurons in artificial neural networks) of the model. The model (e.g. a naive Bayes classifier) is trained on the training data set using a supervised learning method, for example using optimization methods such as gradient descent or stochastic gradient descent. In practice, the training data set often consists of pairs of an input vector (or scalar) and the correspo ...
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