Accelerating Information Retrieval from Profile Hidden Markov Model Databases.

ABSTRACT: Profile Hidden Markov Model (Profile-HMM) is an efficient statistical approach to represent protein families. Currently, several databases maintain valuable protein sequence information as profile-HMMs. There is an increasing interest to improve the efficiency of searching Profile-HMM databases to detect sequence-profile or profile-profile homology. However, most efforts to enhance searching efficiency have been focusing on improving the alignment algorithms. Although the performance of these algorithms is fairly acceptable, the growing size of these databases, as well as the increasing demand for using batch query searching approach, are strong motivations that call for further enhancement of information retrieval from profile-HMM databases. This work presents a heuristic method to accele

SUBMITTER: Tamimi A 

PROVIDER: S-EPMC5119741 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature