A Review of Software Tools for Pathway Crosstalk Inference

E-ISSN： 2212-392x|13|1|64-72

ISSN： 1574-8936

Source： Current Bioinformatics, Vol.13, Iss.1, 2018-02, pp. : 64-72

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Abstract

Background: We are living in an era that is in general characterized by a lot of data but littleinformation. An enormous amount of biological data collected over several years is now presented asannotations and databases. In this context, all this data properly combined and grouped has greatpotential for enabling novel discoveries which would then, finally and hopefully, lead to advances inbiology and medicine. The inference of different kinds of relations between pathways constitutes achallenging step towards the analysis of all these sources of biological data.

Objective: This review article aims at outlining several methods that analyze associations betweenpathways starting from different sources of information, namely the internet, databases, and/or geneexpression data.

Methods: The article consists of a summary of the most important methods for pathway networksinference and arranges them according to the data they use as well as the findings they provide.

Results: The advantages and drawbacks of each considered methodology are presented, as well as ataxonomy tree and summary table as an overview of the discussion.

Conclusion: The methods explained in this paper consist especially of those that explore the concept ofassociations between pathways using microarray experimental data and/or topological or curatedinformation. Each strategy was introduced, classified and analyzed.

The identification of different kinds of associations between pathways plays a central role in systemsbiology, revealing information which is undetectable at a gene level. Therefore, a comprehensibleunderstanding of the benefits and limitations of these approaches could be the key to the development ofnew computational strategies for genome-wide analysis.