A search engine to identify pathway genes from expression data on multiple organisms

doi:10.1186/1752-0509-1-20

BMC Systems Biology

Volume 1

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Methodology article

A search engine to identify pathway genes from expression data on multiple organisms

Chunnuan Chen¹^* , Matthew T Weirauch¹^* , Corey C Powell¹ , Alexander C Zambon² and Joshua M Stuart¹

¹Department of Biomolecular Engineering, University of California, Santa Cruz, California, 95064, USA

²Department of Medicine, Gladstone Institute of Cardiovascular Disease, San Francisco, California 94158, USA

author email corresponding author email* Contributed equally

BMC Systems Biology 2007, 1:20doi:10.1186/1752-0509-1-20


Published:	4 May 2007

Additional files

Additional file 1:

Appendix. Discussion of related work and proof of correctness of order statistics implementation.

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Additional file 7:

Table S2. The query list of genes for the Calcium Channels and Collagens GenMAPP pathways.

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Additional file 10:

Table S5. Summary of significant cis-regulatory motifs identified in the Collagens and Calcium Channels search results.

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Additional file 11:

Table S6. Sequences of potential cis-regulatory binding sites of transcription factors identified in the Calcium Channels search results.

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Additional file 12:

Table S7. Sequences of potential cis-regulatory binding sites identified in the Collagens search results.

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Additional file 13:

Table S8. Conservation of predicted binding sites in the Collagens search result.

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Additional file 2:

Figure S1. Precision-recall results of the MSGR run on the GenMAPP test pathways. Plotted are the same results as shown in Figure 5A of the text, but the precision estimates have here been augmented to include standard error bars to show the variability of the MSGR's performance across the pathways.

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Additional file 3:

Figure S2. Robustness of the Collagens search result to various fractions of held-out data.

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Additional file 4:

Figure S3. Performance of single-species search using query sets restricted to conserved genes.

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Additional file 5:

Figure S4. Performance as a function of orthology prediction error.

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Additional file 6:

Table S1. The pathways tested in the study.

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Additional file 14:

Table S9. Pathways for which accurate predictions with the MSGR could be made.

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Additional file 8:

Table S3. The top 500 genes returned by the MSGR search at the Animal node for the Calcium Channels GenMAPP pathway.

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Additional file 9:

Table S4. The top 500 genes returned by the MSGR search at the Animal node for the Collagen GenMAPP pathway.