Abstract—It has become increasingly clear that signalling pathways are extensively interconnected and are embedded in networks with common protein components. These components do not exist in isolation but may gather together to form crosstalk modules. Constructing these crosstalk modules has emerged as a good method to understand the mechanisms underlying the propagation of transduction signals in cell. In this paper, we have presented an advancement of the method, which is chiefly used to integrate multiple topological and functional data to detect crosstalk modules between nuclear factor kappa B (NF-kB), p53 and theG1/S phase of the cell cycle systems. Applying the Expectation Maximization (EM) clustering algorithm, our results were comparable to the k-means algorithm. The EM algorithm as a soft clustering method is able to distinguish overlapping parts among clusters, and here we show that it is potentially more effective than the k-means algorithm in detecting the cross talking modules involved in the network interactions between the two systems NF-kB and p53. In addition, the biological analyses support our findings, and propose testable hypotheses to which the functional networks are involved in along with their associated human diseases.

Index Terms—Cross talk, Multi-relational Clustering, Functional modules, Signaling network.

Thanh-Phuong Nguyen is with The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Piazza Manci 17, 38123, Povo (Trento), Italy. (phone: +39 0461 282811, fax: +39 0461 282814; e-mail: nguyen@ cosbi.eu).
Adaoha E. C. Ihekwaba is with Cambridge Centre for Brain Repair, University of Cambridge, Forvie Site, Robinson Way, Cambridge, CB2 0PY, UK. (e-mail: aeci3@cam.ac.uk).
Corrado Priami is with The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Piazza Manci 17, 38123, Povo (Trento), Italy and University of Trento, via Belenzani, 12 I-38122 Trento, Italy. (e-mail: priami@ cosbi.eu).

Cite: Thanh-Phuong Nguyen, Adaoha E. C. Ihekwaba, and Corrado Priami, "EM Clustering based Approach to Decipher Functional Modules in Cross-Talking Signaling systems," International Journal of Bioscience, Biochemistry and Bioinformatics vol. 1, no. 1, pp. 1-9, 2011.