title: Sensitive protein comparisons with profiles and hidden Markov models.
abstract: Sequence database searches have become an important tool for the life sciences in general and for gene discovery-driven biotechnology in particular. Both the functional assignment of newly found proteins and the mining of genome databases for functional candidates are equally important tasks typically addressed by database searches. Sensitivity and reliability of the search methods are of crucial importance. The overall performance of sequence alignments and database searches can be enhanced considerably, when profiles or hidden Markov models (HMMs) derived from protein families are used as query objects instead of single sequences. This review discusses the concept of profiles, generalised profiles and profile-HMMs, the methods how they are constructed and the scope of possible applications in gene discovery and gene functional assignment.
authors.affiliation: Bioinformatics & Gene Discovery Group, MEMOREC Stoffel GmbH, Köln, Germany. Kay.hoffmann@memorec.com
authors.forename: K
authors.initials: K
authors.lastname: Hofmann
mesh_terms: D000595:Amino Acid Sequence; D019295:Computational Biology; D016208:Databases, Factual; D006801:Humans; D008390:Markov Chains; D008969:Molecular Sequence Data; D011506:Proteins / Q000737:chemistry / Q000235:genetics*; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000706:statistics & numerical data*
chemical_list: D011506:Proteins