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Capturing context-specific regulation in molecular interaction networks
Örebro University, School of Medical Sciences.ORCID iD: 0000-0003-2437-1300
Örebro University, School of Medical Sciences.ORCID iD: 0000-0002-7173-5579
2018 (English)In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 19, no 1, article id 539Article in journal (Refereed) Published
Abstract [en]

Background: Molecular profiles change in response to perturbations. These changes are coordinated into functional modules via regulatory interactions. The genes and their products within a functional module are expected to be differentially expressed in a manner coherent with their regulatory network. This perspective presents a promising approach to increase precision in detecting differential signals as well as for describing differential regulatory signals within the framework of a priori knowledge about the underlying network, and so from a mechanistic point of view.

Results: We present Coherent Network Expression (CoNE), an effective procedure for identifying differentially activated functional modules in molecular interaction networks. Differential gene expression is chosen as example, and differential signals coherent with the regulatory nature of the network are identified. We apply our procedure to systematically simulated data, comparing its performance to alternative methods. We then take the example case of a transcription regulatory network in the context of particle-induced pulmonary inflammation, recapitulating and proposing additional candidates to previously obtained results. CoNE is conveniently implemented in an R-package along with simulation utilities.

Conclusion: Combining coherent interactions with error control on differential gene expression results in uniformly greater specificity in inference than error control alone, ensuring that captured functional modules constitute real findings.

Place, publisher, year, edition, pages
BioMed Central, 2018. Vol. 19, no 1, article id 539
Keywords [en]
Activated subnetwork, Coherent differential expression, Differential regulation, Error control, Functional module, Molecular network
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:oru:diva-65214DOI: 10.1186/s12859-018-2513-7ISI: 000454209300003PubMedID: 30577761Scopus ID: 2-s2.0-85058920164OAI: oai:DiVA.org:oru-65214DiVA, id: diva2:1185427
Funder
Knowledge Foundation, 20110225Available from: 2018-02-24 Created: 2018-02-24 Last updated: 2019-01-11Bibliographically approved

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Rush, StephenRepsilber, Dirk

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CiteExportLink to record
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  • apa
  • harvard1
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