Literature DB >> 26621463

Predicting Functional Interactions Among Genes in Prokaryotes by Genomic Context.

G Moreno-Hagelsieb1, G Santoyo2.   

Abstract

Genomic context methods for finding functions of unannotated genes were implemented very early after the publication of the first few prokaryotic genomes. The ideas behind these methods include gene fusions, conservation of gene adjacency, and the patters of co-occurrence of genes across available genomes. A later addition was the prediction of features related to functional organization, such as operons, stretches of genes co-transcribed into a single messenger RNA. The ideas behind these methods tend to be easy to understand, while the strategies for transforming those basic ideas into predictions can vary in complexity, mostly because genes whose products are known to functionally interact vary in the way they relate to those basic ideas. We present here a view of genomic context methods for predicting functional interactions, with simple examples of their implementation as compared and evaluated using genes whose products are known to functionally interact.

Keywords:  Comparative genomics; Conservation of gene order; Gene fusion; Interactome; Operon rearrangement; Operons; Phylogenetic profiles; Prokaryotes

Mesh:

Year:  2015        PMID: 26621463     DOI: 10.1007/978-3-319-23603-2_5

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  3 in total

Review 1.  Mechanisms of Theta Plasmid Replication in Enterobacteria and Implications for Adaptation to Its Host.

Authors:  Jay W Kim; Vega Bugata; Gerardo Cortés-Cortés; Giselle Quevedo-Martínez; Manel Camps
Journal:  EcoSal Plus       Date:  2020-11

2.  A Comprehensive Evolutionary Scenario of Cell Division and Associated Processes in the Firmicutes.

Authors:  Pierre S Garcia; Wandrille Duchemin; Jean-Pierre Flandrois; Simonetta Gribaldo; Christophe Grangeasse; Céline Brochier-Armanet
Journal:  Mol Biol Evol       Date:  2021-05-19       Impact factor: 16.240

Review 3.  NusG, an Ancient Yet Rapidly Evolving Transcription Factor.

Authors:  Bing Wang; Irina Artsimovitch
Journal:  Front Microbiol       Date:  2021-01-08       Impact factor: 5.640

  3 in total

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