Literature DB >> 17040488

Integration of omics data: how well does it work for bacteria?

Sigrid C J De Keersmaecker1, Inge M V Thijs, Jos Vanderleyden, Kathleen Marchal.   

Abstract

In the current omics era, innovative high-throughput technologies allow measuring temporal and conditional changes at various cellular levels. Although individual analysis of each of these omics data undoubtedly results into interesting findings, it is only by integrating them that gaining a global insight into cellular behaviour can be aimed at. A systems approach thus is predicated on data integration. However, because of the complexity of biological systems and the specificities of the data-generating technologies (noisiness, heterogeneity, etc.), integrating omics data in an attempt to reconstruct signalling networks is not trivial. Developing its methodologies constitutes a major research challenge. Besides for their intrinsic value towards health care, environment and industry, prokaryotes are ideal model systems to further develop these methods because of their lower regulatory complexity compared with eukaryotes, and the ease with which they can be manipulated. Several successful examples outlined in this review already show the potential of the systems approach for both fundamental and industrial applications, which would be time-consuming or impossible to develop solely through traditional reductionist approaches.

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Substances:

Year:  2006        PMID: 17040488     DOI: 10.1111/j.1365-2958.2006.05453.x

Source DB:  PubMed          Journal:  Mol Microbiol        ISSN: 0950-382X            Impact factor:   3.501


  13 in total

1.  Evolving systems biology approaches to understanding non-coding RNAs in pulmonary hypertension.

Authors:  Lloyd D Harvey; Stephen Y Chan
Journal:  J Physiol       Date:  2018-09-02       Impact factor: 5.182

Review 2.  Plant systems biology: insights, advances and challenges.

Authors:  Bhavisha P Sheth; Vrinda S Thaker
Journal:  Planta       Date:  2014-03-27       Impact factor: 4.116

3.  An Introduction to Programming for Bioscientists: A Python-Based Primer.

Authors:  Berk Ekmekci; Charles E McAnany; Cameron Mura
Journal:  PLoS Comput Biol       Date:  2016-06-07       Impact factor: 4.475

4.  Gene networks in Drosophila melanogaster: integrating experimental data to predict gene function.

Authors:  James C Costello; Mehmet M Dalkilic; Scott M Beason; Jeff R Gehlhausen; Rupali Patwardhan; Sumit Middha; Brian D Eads; Justen R Andrews
Journal:  Genome Biol       Date:  2009-09-16       Impact factor: 13.583

Review 5.  Salmonella pathogenicity and host adaptation in chicken-associated serovars.

Authors:  Steven L Foley; Timothy J Johnson; Steven C Ricke; Rajesh Nayak; Jessica Danzeisen
Journal:  Microbiol Mol Biol Rev       Date:  2013-12       Impact factor: 11.056

6.  Delineation of the Salmonella enterica serovar Typhimurium HilA regulon through genome-wide location and transcript analysis.

Authors:  Inge M V Thijs; Sigrid C J De Keersmaecker; Abeer Fadda; Kristof Engelen; Hui Zhao; Michael McClelland; Kathleen Marchal; Jos Vanderleyden
Journal:  J Bacteriol       Date:  2007-05-04       Impact factor: 3.490

7.  Meta Analysis of Gene Expression Data within and Across Species.

Authors:  Ana C Fierro; Filip Vandenbussche; Kristof Engelen; Yves Van de Peer; Kathleen Marchal
Journal:  Curr Genomics       Date:  2008-12       Impact factor: 2.236

8.  An emerging cyberinfrastructure for biodefense pathogen and pathogen-host data.

Authors:  C Zhang; O Crasta; S Cammer; R Will; R Kenyon; D Sullivan; Q Yu; W Sun; R Jha; D Liu; T Xue; Y Zhang; M Moore; P McGarvey; H Huang; Y Chen; J Zhang; R Mazumder; C Wu; B Sobral
Journal:  Nucleic Acids Res       Date:  2007-11-04       Impact factor: 16.971

9.  A proposed minimum skill set for university graduates to meet the informatics needs and challenges of the "-omics" era.

Authors:  Tin Wee Tan; Shen Jean Lim; Asif M Khan; Shoba Ranganathan
Journal:  BMC Genomics       Date:  2009-12-03       Impact factor: 3.969

10.  Genome scale modeling in systems biology: algorithms and resources.

Authors:  Ali Najafi; Gholamreza Bidkhori; Joseph H Bozorgmehr; Ina Koch; Ali Masoudi-Nejad
Journal:  Curr Genomics       Date:  2014-04       Impact factor: 2.236

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