LocalAli: an evolutionary-based local alignment approach to identify functionally conserved modules in multiple networks | Zendy

Jialu Hu | Zendy; Knut Reinert | Zendy

Open Access

LocalAli: an evolutionary-based local alignment approach to identify functionally conserved modules in multiple networks

Author(s) -

Jialu Hu,

Knut Reinert

Publication year - 2014

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btu652

Subject(s) - scalability , computer science , heuristic , evolutionary algorithm , identification (biology) , simulated annealing , code (set theory) , source code , data mining , theoretical computer science , smith–waterman algorithm , artificial intelligence , machine learning , sequence alignment , biology , set (abstract data type) , biochemistry , botany , database , gene , programming language , peptide sequence , operating system

Sequences and protein interaction data are of significance to understand the underlying molecular mechanism of organisms. Local network alignment is one of key systematic ways for predicting protein functions, identifying functional modules and understanding the phylogeny from these data. Most of currently existing tools, however, encounter their limitations, which are mainly concerned with scoring scheme, speed and scalability. Therefore, there are growing demands for sophisticated network evolution models and efficient local alignment algorithms.

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