Multiple Sequence Alignment Using Probcons and Probalign
Author:
- 23 August 2013
- book chapter
- Published by Springer Nature
- Vol. 1079, 147-153
Abstract
Sequence alignment remains a fundamental task in bioinformatics. The literature contains programs that employ a host of exact and heuristic strategies available in computer science. Probcons was the first program to construct maximum expected accuracy sequence alignments with hidden Markov models and at the time of its publication achieved the highest accuracies on standard protein multiple alignment benchmarks. Probalign followed this strategy except that it used a partition function approach instead of hidden Markov models. Several programs employing both strategies have been published since then. In this chapter we describe Probcons and Probalign.Keywords
This publication has 18 references indexed in Scilit:
- PLAST-ncRNA: Partition function Local Alignment Search Tool for non-coding RNA sequencesNucleic Acids Research, 2010
- Searching for evolutionary distant RNA homologs within genomic sequences using partition function posterior probabilitiesBMC Bioinformatics, 2008
- Probalign: multiple sequence alignment using partition function posterior probabilitiesBioinformatics, 2006
- BAliBASE 3.0: Latest developments of the multiple sequence alignment benchmarkProteins: Structure, Function, and Bioinformatics, 2005
- ProbCons: Probabilistic consistency-based multiple sequence alignmentGenome Research, 2005
- MAFFT version 5: improvement in accuracy of multiple sequence alignmentNucleic Acids Research, 2005
- Predicting protein functional sites with phylogenetic motifsProteins: Structure, Function, and Bioinformatics, 2004
- MUSCLE: multiple sequence alignment with high accuracy and high throughputNucleic Acids Research, 2004
- T-coffee: a novel method for fast and accurate multiple sequence alignment 1 1Edited by J. ThorntonJournal of Molecular Biology, 2000
- A reliable sequence alignment method based on probabilities of residue correspondencesProtein Engineering, Design and Selection, 1995