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The GeneMark.hmm algorithm (1998) was designed to improve accuracy of prediction of short genes and gene starts. The idea was to use the inhomogeneous Markov chain models introduced in GeneMark for computing likelihoods of the sequences emitted by the states of a hidden Markov model, or rather semi-Markov HMM, or generalized HMM describing the genomic sequence.
Its name stands for Prokaryotic Dynamic Programming Genefinding Algorithm. It is based on log-likelihood functions and does not use Hidden or Interpolated Markov Models. Prokaryotes, Metagenomes (metaProdigal) [4] AUGUSTUS: Eukaryote gene predictor: Eukaryotes [5] BGF Hidden Markov model (HMM) and dynamic programming based ab initio gene ...
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.
General GFF3 structure Position index Position name Description 1 seqid The name of the sequence where the feature is located. 2 source The algorithm or procedure that generated the feature.
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Mark Borodovsky (Russian: Марк Бородовский) is a Regents' Professor at the Join Wallace H. Coulter Department of Biomedical Engineering of Georgia Institute of Technology and Emory University and Director of the Center for Bioinformatics and Computational Genomics at Georgia Tech. [1] He has also been a Chair of the Department of Bioinformatics at the Moscow Institute of Physics ...
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