What kind of scientists would we be if not inventing something? Taste the fruits of our labour.

CLAIM - coupling co-expression data and protein-protein interaction networks for functional protein analysis

CLAIM (CLusterAnalysis Integration Method) is a new method for integrating co-expression data obtained through microarray experiments (MA) and protein-protein interaction (PPI) network data. Microarray and PPI data are separately clustered; the clusters are then merged in a special graph; cliques of this graph would identify a group of functionally related proteins. The biological insight provided by these groups is analyzed on the basis of co-localization and mRNA developmental expression, pointing out the new information that can be obtained by this method.

CLAIM can be also used to assign proteins whose functional role is unknown to pathways using the cliques that are strongly associated with known pathways. The basic assumption is that, if a protein belongs to a clique and the other proteins in that clique are in a known pathway, then that protein is likely to belong to that pathway. Based on this assumption, pathway assignment was performed through a score prediction function, based on the presence of a protein in pathway enriched cliques.
The prediction power of the algorithm appears to be sufficiently high to make this method a useful semi-automated tool for protein functional analysis.

Method CLAIM has been tested on the model organism Arabidopsis thaliana.

For more detailed information please read CLAIM README.

Daniele Santoni3, Aleksandra Swiercz1,4, Agnieszka Żmieńko1,4, Marta Kasprzak1,4, Marek Blazewicz1,2, Paola Bertolazzi3, Giovanni Felici3, An Integrated Approach (CLuster Analysis Integration Method) to Combine Expression Data and Protein–Protein Interaction Networks in Agrigenomics: Application on Arabidopsis thaliana, OMICS: A Journal of Integrative Biology. January 2014, 18(2): 155-165. doi:10.1089/omi.2013.0050.
1 Institute of Computing Science,Poznan University of Technology, Poznan, Poland. 
2 Poznan Supercomputing and Networking Center, Poznan, Poland. 
3 Institute for Systems Analysis and Computer Science “Antonio Ruberti”, National Research Council of Italy, Rome, Italy. 
4 Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland.