Literature DB >> 11932011

Identifying functional links between genes using conserved chromosomal proximity.

Itai Yanai1, Joseph C Mellor, Charles DeLisi.   

Abstract

Conservation of proximity of a pair of genes across multiple genomes generally indicates that their functions could be linked. Here, we present a systematic evaluation using 42 complete microbial genomes from 25 phylogenetic groups to test the reliability of this observation in predicting function for genes. We find a relationship between the number of phylogenetic groups in which a gene pair is proximate and the probability that the pair belongs to a common pathway. Our method produces 1586 links between ortholog families substantiated by observed proximity in genomes representing at least three phylogenetic groups. Of the pairs annotated in the KEGG database, 80% are in the same biological pathway in KEGG.

Mesh:

Year:  2002        PMID: 11932011     DOI: 10.1016/s0168-9525(01)02621-x

Source DB:  PubMed          Journal:  Trends Genet        ISSN: 0168-9525            Impact factor:   11.639


  32 in total

1.  Whole-genome annotation by using evidence integration in functional-linkage networks.

Authors:  Ulas Karaoz; T M Murali; Stan Letovsky; Yu Zheng; Chunming Ding; Charles R Cantor; Simon Kasif
Journal:  Proc Natl Acad Sci U S A       Date:  2004-02-23       Impact factor: 11.205

Review 2.  Co-evolution analysis on endocrine research: a methodological approach.

Authors:  Tonghai Dou; Shuai Chen; Chaoneng Ji; Yi Xie; Yumin Mao
Journal:  Endocrine       Date:  2005-11       Impact factor: 3.633

Review 3.  Practical and theoretical advances in predicting the function of a protein by its phylogenetic distribution.

Authors:  Philip R Kensche; Vera van Noort; Bas E Dutilh; Martijn A Huynen
Journal:  J R Soc Interface       Date:  2008-02-06       Impact factor: 4.118

4.  Genome data mining and soil survey for the novel group 5 [NiFe]-hydrogenase to explore the diversity and ecological importance of presumptive high-affinity H(2)-oxidizing bacteria.

Authors:  Philippe Constant; Soumitra Paul Chowdhury; Laura Hesse; Jennifer Pratscher; Ralf Conrad
Journal:  Appl Environ Microbiol       Date:  2011-07-08       Impact factor: 4.792

5.  Statistics for approximate gene clusters.

Authors:  Katharina Jahn; Sascha Winter; Jens Stoye; Sebastian Böcker
Journal:  BMC Bioinformatics       Date:  2013-12-13       Impact factor: 3.169

6.  Identifying metabolic enzymes with multiple types of association evidence.

Authors:  Peter Kharchenko; Lifeng Chen; Yoav Freund; Dennis Vitkup; George M Church
Journal:  BMC Bioinformatics       Date:  2006-03-29       Impact factor: 3.169

7.  Gene function prediction based on genomic context clustering and discriminative learning: an application to bacteriophages.

Authors:  Jason Li; Saman K Halgamuge; Christopher I Kells; Sen-Lin Tang
Journal:  BMC Bioinformatics       Date:  2007-05-22       Impact factor: 3.169

Review 8.  'Unknown' proteins and 'orphan' enzymes: the missing half of the engineering parts list--and how to find it.

Authors:  Andrew D Hanson; Anne Pribat; Jeffrey C Waller; Valérie de Crécy-Lagard
Journal:  Biochem J       Date:  2009-12-14       Impact factor: 3.857

9.  Classifying genes to the correct Gene Ontology Slim term in Saccharomyces cerevisiae using neighbouring genes with classification learning.

Authors:  Heather A Amthauer; Costas Tsatsoulis
Journal:  BMC Genomics       Date:  2010-05-28       Impact factor: 3.969

10.  Genomic gene clustering analysis of pathways in eukaryotes.

Authors:  Jennifer M Lee; Erik L L Sonnhammer
Journal:  Genome Res       Date:  2003-04-14       Impact factor: 9.043

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