EGM: encapsulated gene-by-gene matching to identify gene orthologs and homologous segments in genomes | Zendy

Khalid Mahmood | Zendy; Arun S. Konagurthu | Zendy; Jiangning Song | Zendy; Ashley M. Buckle | Zendy; Geoffrey I. Webb | Zendy; James C. Whisstock | Zendy

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EGM: encapsulated gene-by-gene matching to identify gene orthologs and homologous segments in genomes

Author(s) -

Khalid Mahmood,

Arun S. Konagurthu,

Jiangning Song,

Ashley M. Buckle,

Geoffrey I. Webb,

James C. Whisstock

Publication year - 2010

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/btq339

Subject(s) - genome , gene , biology , computational biology , context (archaeology) , genetics , gene prediction , bipartite graph , identification (biology) , orthologous gene , matching (statistics) , human genome , graph , computer science , theoretical computer science , mathematics , paleontology , statistics , botany

Identification of functionally equivalent genes in different species is essential to understand the evolution of biological pathways and processes. At the same time, identification of strings of conserved orthologous genes helps identify complex genomic rearrangements across different organisms. Such an insight is particularly useful, for example, in the transfer of experimental results between different experimental systems such as Drosophila and mammals.

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