Crosstalk Pathway Inference using Topological Information and Biclustering of Gene Expression Data

DUSSAUT, JULIETA SOL; GALLO, CRISTIAN A.; CECCHINI, ROCÍO L.; CARBALLIDO, JESSICA A.; PONZONI, IGNACIO

BIOSYSTEMS

ELSEVIER SCI LTD

Lugar: Amsterdam; Año: 2016 vol. 150 p. 1 - 12

0303-2647

tDetection of crosstalks among pathways is a challenging task, which requires the identification of differ-ent types of interactions associated with cellular processes. A common strategy used in bioinformaticsconsists in extrapolating pathway associations from the pairwise analysis of some genes related to them,using gene expression data and topological information. PET, the method proposed in this paper, goes astep further by incorporating a strategy for the detection of correlation across conditions between dif-ferentially expressed genes based on biclustering analysis. In order to evaluate the performance of thisnew approach, a comparison with two recently published algorithms was carried out. The methods werecontrasted in the inference of pathway associations from Alzheimer disease datasets, where the newproposal presents a higher crosstalk discoveries? rate. Finally, the analysis of the biological relevance ofthe pathway associations inferred by PET has shown the soundness of the extracted knowledge.