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Comparative ab initio prediction of gene structures using pair HMMs

Item Type:Article
Title:Comparative ab initio prediction of gene structures using pair HMMs
Creators Name:Meyer, I.M. and Durbin, R.
Abstract:We present a novel comparative method for the ab initio prediction of protein coding genes in eukaryotic genomes. The method simultaneously predicts the gene structures of two un-annotated input DNA sequences which are homologous to each other and retrieves the subsequences which are conserved between the two DNA sequences. It is capable of predicting partial, complete and multiple genes and can align pairs of genes which differ by events of exon-fusion or exon-splitting. The method employs a probabilistic pair hidden Markov model. We generate annotations using our model with two different algorithms: the Viterbi algorithm in its linear memory implementation and a new heuristic algorithm, called the stepping stone, for which both memory and time requirements scale linearly with the sequence length. We have implemented the model in a computer program called DOUBLESCAN. In this article, we introduce the method and confirm the validity of the approach on a test set of 80 pairs of orthologous DNA sequences from mouse and human. More information can be found at: http://www.sanger.ac.uk/Software/analysis/doublescan/
Keywords:Algorithms, DNA Sequence Analysis, Exons, Gene Expression Regulation, Genetic Models, Markov Chains, Nucleic Acid Databases, Proteomics, Reproducibility of Results, Sensitivity and Specificity, Sequence Alignment, Software, Animals, Mice
Source:Bioinformatics
ISSN:1367-4803
Volume:18
Number:10
Page Range:1309-1318
Date:October 2002
Official Publication:https://doi.org/10.1093/bioinformatics/18.10.1309
PubMed:View item in PubMed

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