| Literature DB >> 7497123 |
S R Eddy1, G Mitchison, R Durbin.
Abstract
We introduce a maximum discrimination method for building hidden Markov models (HMMs) of protein or nucleic acid primary sequence consensus. The method compensates for biased representation in sequence data sets, superseding the need for sequence weighting methods. Maximum discrimination HMMs are more sensitive for detecting distant sequence homologs than various other HMM methods or BLAST when tested on globin and protein kinase catalytic domain sequences.Mesh:
Substances:
Year: 1995 PMID: 7497123 DOI: 10.1089/cmb.1995.2.9
Source DB: PubMed Journal: J Comput Biol ISSN: 1066-5277 Impact factor: 1.479