ProbCons: Probabilistic consistency-based multiple sequence alignment.

By Chuong B. Do, Mahathi S. Mahabhashyam, Michael Brudno, Serafim Batzoglou. Genome Research, 2005

1,197 citations recorded by the source corpus.

To study gene evolution across a wide range of organisms, biologists need accurate tools for multiple sequence alignment of protein families. Obtaining accurate alignments, however, is a difficult computational problem because of not only the high computational cost but also the lack of proper objective functions for measuring alignment quality. In this paper, we introduce probabilistic consistency, a novel scoring function for multiple sequence comparisons. We present ProbCons, a practical tool for progressive protein multiple sequence alignment based on probabilistic consistency, and evaluate its performance on several standard alignment benchmark data sets. On the BAliBASE, SABmark, and PREFAB benchmark alignment databases, ProbCons achieves statistically significant improvement over other leading methods while maintaining practical speed. ProbCons is publicly available as a Web resource.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2ee638dbd3a8083d3aa20fd45c240f1661868e74

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Citations in the corpus

Inferring Stabilizing Mutations from Protein Phylogenies: Application to Influenza Hemagglutinin (2009, methodology): “The protein sequences of the homologs were aligned using ProbCons [76] (for cold shock protein, ribonuclease HI, and thioredoxin) or MUSCLE [77] (for influenza hemagglutinin).”
Large-Scale Determination of Sequence, Structure, and Function Relationships in Cytosolic Glutathione Transferases across the Biosphere (2014, methodology): “Construction of Multiple Sequence Alignments Multiple sequence alignments (MSAs) were constructed using ProbCons [47] or PROMALS3D [48,49], a program that PLOS Biology | www.plosbiology.org 4 April 2014 | Volume 12 | Issue 4 | e1001843 incorporates 3D structure into the calculations to help guide th”
Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments. (2007, methodology): “…have selected ClustalW as the currently most used progressive alignment method (Thompson et al., 1994) and Mafft (Katoh et al., 2005) and Probcons (Do et al., 2005) as examples of more recently developed methods that have been shown to obtain very high scores in terms of alignment accuracy…”
Recent developments in the MAFFT multiple sequence alignment program (2008, methodology): “Iterative refinement method with consistency andWSP scoresçG-INS-i T-Coffee [64], ProbCons [68] and other methods [69, 70] take an entirely different approach to overcome the drawback of the progressive method by using a consistency criterion, in which an MSA consistent with pairwise alignments is j”
progressiveMauve: Multiple Genome Alignment with Gene Gain, Loss and Rearrangement (2010, methodology): “Multiple alignment methods based on probabilistic consistency have demonstrated great promise in the context of amino-acid alignment [75] and aligning collinear genomic regions [33], and in principle, could be extended to genome alignment with rearrangement.”
COBALT: constraint-based alignment tool for multiple protein sequences (2007, methodology): “This has led to an arsenal of approximation techniques from graph theory (Gupta et al ., 1995; Kobayashi and Imai, 1998) combinatorial optimization (Notredame and Higgins, 1996; Zhong, 2002) and probability theory (Do et al ., 2005).”
A fast structural multiple alignment method for long RNA sequences (2008, background): “(xk ~ ym|x, y) and (xl ~ yn|x, y) are the posterior probabilities modified by probability consistency transformation [32], which is computed as follows.”
LocARNA-P: accurate boundary prediction and improved detection of structural RNAs. (2012, methodology): “While approaches like RAF (Do et al. 2005) and ExpaRNA (Heyne et al. 2009) aim at speeding up Sankoff-style alignment by means of further heuristics, the novelty of LocARNA-P is the efficient calculation of match probabilities and reliabilities (STARs), which introduces a novel quality to…”
SeaView version 4: A multiplatform graphical user interface for sequence alignment and phylogenetic tree building. (2010, background): “Likewise, SeaView’s interface to Probcons (Do et al. 2005) is straightforward: %f:pir.”
De novo identification of highly diverged protein repeats by probabilistic consistency (2008, methodology): “The first is specialized in detecting repeats in fibrous proteins and does not allow for insertions within ( Coward and Drablos, 1998 ) or between repeat units (Gruber et al., 2005; Lupas et al., 1991; McLachlan and Stewart, 1976; Newman and Cooper, 2007).”
PROMALS: towards accurate multiple sequence alignments of distantly related proteins (2007, methodology): “Further improvement comes with a probabilistic treatment of consistency via pairwise hidden Markov models (HMMs), as first implemented in ProbCons (Do et al., 2005).”
Accurate multiple sequence alignment of transmembrane proteins with PSI-Coffee (2012, methodology): “The pair-HMM is adapted from the ProbCons pairHMM [14] in order to deal with profiles.”
The MPI Bioinformatics Toolkit for protein sequence analysis (2006, methodology): “The alignment section includes the well-known, popular multiple alignment program ClustalW (14), together with the more recently developed multiple alignment methods ProbCons (15), MUSCLE (16) and MAFFT (17).”
T-Coffee: a web server for the multiple sequence alignment of protein and RNA sequences using structural information and homology extension (2011, methodology): “The ﬁrst version was using a combination of ClustalW all against all pair-wise alignments combined with Lalign all against all local alignments, the current version uses all against all pair-wise alignments computed with a pair HMM (9).”