Research article
Evaluation of a Bayesian inference network for ligand-based virtual screening
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* Corresponding author: Peter Willett p.willett@sheffield.ac.uk
Krebs Institute for Biomolecular Research, Departments of Chemistry and of Information Studies, University of Sheffield, Sheffield, S10 2TN, UK
Journal of Cheminformatics 2009, 1:5 doi:10.1186/1758-2946-1-5
Published: 29 April 2009Additional files
Additional file 1:
Table S1. Recall of actives in the top-1% of the ranked MDDR database using the Bayesian SUM inference network and Tanimoto searches. The belief functions used are STD (for the standard function used in the InQuery project), OKA (for that used in the OKAPI project), SMO (for the language-modeling smoothing function) and SMOL (for the natural logarithm of the smoothing function). Each pair of columns lists the mean and the standard deviation for the percentage recall.
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Additional file 2:
Table S2. Recall of actives in the top-1% of the ranked MDDR database using the Bayesian WSUM inference network and Tanimoto searches. Details as for Additional file 1.
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Additional file 3:
Table S3. Recall of actives in the top-1% of the ranked WOMBAT database using the Bayesian SUM inference network and Tanimoto searches. Details as for Additional file 1.
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Table S4. Recall of actives in the top-1% of the ranked WOMBAT database using the Bayesian WSUM inference network and Tanimoto searches. Details as for Additional file 1.
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Additional file 5:
Table S5. Recall of actives in the top-1% of the ranked MDDR-HOM database using the Bayesian SUM inference network and Tanimoto searches. Details as for Additional file 1.
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Table S6. Recall of actives in the top-1% of the ranked MDDR-HOM database using the Bayesian WSUM inference network and Tanimoto searches. Details as for Additional file 1.
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Additional file 7:
Table S7. Recall of actives in the top-1% of the ranked MDDR-HET database using the Bayesian SUM inference network and Tanimoto searches. Details as for Additional file 1.
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Additional file 8:
Table S8. Recall of actives in the top-1% of the ranked MDDR-HET database using the Bayesian WSUM inference network and Tanimoto searches. Details as for Additional file 1.
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