Probabilistic prediction and ranking of human protein-protein interactions

doi:10.1186/1471-2105-8-239

BMC Bioinformatics

Volume 8

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Research article

Probabilistic prediction and ranking of human protein-protein interactions

Michelle S Scott and Geoffrey J Barton

School of Life Sciences Research, College of Life Sciences, University of Dundee, Scotland, UK

author email corresponding author email

BMC Bioinformatics 2007, 8:239doi:10.1186/1471-2105-8-239


Published:	5 July 2007

Additional files

Additional File 1:

High scoring InterPro domain pairs. List of InterPro domain pairs that achieve highest chi-square score of co-occurrence in our set of positive interactors.

Format: XLS Size: 900KB Download file

This file can be viewed with: Microsoft Excel Viewer

Additional File 2:

High scoring post-translational modification pairs. List of high-scoring post-translational modification pairs.

Format: XLS Size: 42KB Download file

This file can be viewed with: Microsoft Excel Viewer

Additional File 3:

All LR400 predicted interactions ranked. All human protein pairs predicted to have a likelihood ratio of interaction greater than 400 and thus a posterior odds ratio of interaction greater than 1.

Format: XLS Size: 3.4MB Download file

This file can be viewed with: Microsoft Excel Viewer

Additional file 4:

Additional methods. In depth description of the calculation of likelihood ratios for the modules.

Format: PDF Size: 40KB Download file

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