Open Access Highly Accessed Method

Discovery of biological networks from diverse functional genomic data

Chad L Myers12, Drew Robson3, Adam Wible1, Matthew A Hibbs12, Camelia Chiriac2, Chandra L Theesfeld4, Kara Dolinski2 and Olga G Troyanskaya12*

Author Affiliations

1 Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ 08544, USA

2 Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, NJ 08544, USA

3 Department of Mathematics, Princeton University, Washington Road, Princeton, NJ 08540, USA

4 Department of Genetics, School of Medicine, Mailstop-S120, Stanford University, Stanford, CA 94305-5120, USA

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Genome Biology 2005, 6:R114  doi:10.1186/gb-2005-6-13-r114

Published: 19 December 2005

Additional files

Additional data file 1:

This file contains the structure and final learned conditional probability tables used for integrating multiple heterogeneous sources of functional genomic data. GeNIe, available at http://genie.sis.pitt.edu/downloads.html webcite, is recommended for viewing the dsl file.

Format: DSL Size: 24KB Download file

Open Data

Additional data file 2:

This file contains a list of pathways and protein complexes that were used to evaluate the performance of bioPIXIE. The source of the group and the number of proteins in each is also included.

Format: TXT Size: 1KB Download file

Open Data

Additional data file 3:

This file contains a comparison of the performance of bioPIXIE to existing methods for biological network recovery. The area under the precision-recall curve (AUC) is computed and plotted separately for each of the 31 evaluation pathways and complexes.

Format: XLS Size: 43KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data