BMC Systems Biology

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A quantitative approach to study indirect effects among disease proteins in the human protein interaction network

Thanh-Phuong Nguyen and Ferenc Jordán*

Author Affiliations

The Microsoft Research - University of Trento, Centre for Computational and Systems Biology, Piazza Manci 17, 38100, Trento, Italy

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BMC Systems Biology 2010, 4:103 doi:10.1186/1752-0509-4-103

Published: 29 July 2010

Additional files

Additional file 1:

Identity of mediator proteins among H proteins causing heart diseases (in columns) and D proteins causing diabetes (in rows). Most of the mediators are IP proteins (in black), there is a single disease protein connecting the other two sets of disease proteins (P12931, belonging to C, in red).

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Additional file 2:

The relative strength of two-step-long indirect interactions (AH,D2) mediated by mediators among H and D. Column sums would give which H protein is mostly influenced by D proteins (P18825), while row sums would give which D protein is mostly influenced by H proteins (P51681). The largest value (0.17983) indicates the strongest indirect effect between the two diseases (corresponding to P09471, see Additional file 1).

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Additional file 3:

The most important mediator proteins are shown among H and O as well as H and D sets of disease proteins, ranked according to their mediation strength M2 (calculated for the DPIP network).

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Additional file 4:

the values and ranks of nD and nB values for the nodes of the PPI, DPIP and IP networks. Also, the nD vs nB relationships and the value rank column diagrams are given for each network.

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Additional file 5:

the count, P-value and identity of H-O mediator proteins chracterized by particular GO categories and terms.

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Additional file 6:

the count, P-value and identity of H-D mediator proteins chracterized by particular GO categories and terms.

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