Cargando…
MUMMALS: multiple sequence alignment improved by using hidden Markov models with local structural information
We have developed MUMMALS, a program to construct multiple protein sequence alignment using probabilistic consistency. MUMMALS improves alignment quality by using pairwise alignment hidden Markov models (HMMs) with multiple match states that describe local structural information without exploiting e...
Autores principales: | Pei, Jimin, Grishin, Nick V. |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2006
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1636350/ https://www.ncbi.nlm.nih.gov/pubmed/16936316 http://dx.doi.org/10.1093/nar/gkl514 |
Ejemplares similares
-
PROMALS3D: a tool for multiple protein sequence and structure alignments
por: Pei, Jimin, et al.
Publicado: (2008) -
Accurate statistical model of comparison between multiple sequence alignments
por: Sadreyev, Ruslan I., et al.
Publicado: (2008) -
Binding site discovery from nucleic acid sequences by discriminative learning of hidden Markov models
por: Maaskola, Jonas, et al.
Publicado: (2014) -
Improving accuracy of multiple sequence alignment algorithms based on alignment of neighboring residues
por: Lu, Yue, et al.
Publicado: (2009) -
PROMALS web server for accurate multiple protein sequence alignments
por: Pei, Jimin, et al.
Publicado: (2007)