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Fast detection of coding regions in short genome sequences: Dragon Promoter Finder Program to recognize vertebrate RNA polymerase II promoters: Vertebrates [7] EasyGene: The gene finder is based on a hidden Markov model (HMM) that is automatically estimated for a new genome. Prokaryotes [8] [9] EuGene: Integrative gene finding: Prokaryotes ...
Component-based data mining and machine learning software suite written in C++, featuring a visual programming front-end for exploratory data analysis and interactive visualization, and Python bindings and libraries for scripting Linux, macOS, Windows: GPL: University of Ljubljana: SAMtools
Integrated Genome Browser (IGB) (pronounced Ig-Bee) [1] is an open-source genome browser, a visualization tool used to observe biologically-interesting patterns in genomic data sets, including sequence data, gene models, alignments, and data from DNA microarrays.
Ab Initio gene prediction is an intrinsic method based on gene content and signal detection. Because of the inherent expense and difficulty in obtaining extrinsic evidence for many genes, it is also necessary to resort to ab initio gene finding, in which the genomic DNA sequence alone is systematically searched for certain tell-tale signs of protein-coding genes.
The fourth is a great example of how interactive graphical tools enable a worker involved in sequence analysis to conveniently execute a variety if different computational tools to explore an alignment's phylogenetic implications; or, to predict the structure and functional properties of a specific sequence, e.g., comparative modelling.
In general, a machine learning system can usually be trained to recognize elements of a certain class given sufficient samples. [30] For example, machine learning methods can be trained to identify specific visual features such as splice sites. [31] Support vector machines have been extensively used in cancer genomic studies. [32]
Eigengenes define robust biomarkers, [12] and can be used as features in complex machine learning models such as Bayesian networks. [13] To find modules that relate to a clinical trait of interest, module eigengenes are correlated with the clinical trait of interest, which gives rise to an eigengene significance measure.
In bioinformatics, GENSCAN is a program to identify complete gene structures in genomic DNA. It is a GHMM-based program that can be used to predict the location of genes and their exon-intron boundaries in genomic sequences from a variety of organisms. The GENSCAN Web server can be found at MIT.