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Computational approaches for the analysis of HTS results face great challenges due to the large quantity of information and significant amounts of erroneous data produced.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In this study, Decision Trees (DT) based models were developed to discriminate compound bioactivities by using their chemical structure fingerprints provided in the PubChem system<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/pubchem.ncbi.nlm.nih.gov\" ext-link-type=\"uri\">http:\/\/pubchem.ncbi.nlm.nih.gov<\/jats:ext-link>. The DT models were examined for filtering biological activity data contained in four assays deposited in the PubChem Bioassay Database including assays tested for 5HT1a agonists, antagonists, and HIV-1 RT-RNase H inhibitors. The 10-fold Cross Validation (CV) sensitivity, specificity and Matthews Correlation Coefficient (MCC) for the models are 57.2~80.5%, 97.3~99.0%, 0.4~0.5 respectively. A further evaluation was also performed for DT models built for two independent bioassays, where inhibitors for the same HIV RNase target were screened using different compound libraries, this experiment yields enrichment factor of 4.4 and 9.7.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Our results suggest that the designed DT models can be used as a virtual screening technique as well as a complement to traditional approaches for hits selection.<\/jats:p><\/jats:sec>","DOI":"10.1186\/1471-2105-9-401","type":"journal-article","created":{"date-parts":[[2008,10,24]],"date-time":"2008-10-24T18:13:17Z","timestamp":1224871997000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":88,"title":["Developing and validating predictive decision tree models from mining chemical structural fingerprints and high\u2013throughput screening data in PubChem"],"prefix":"10.1186","volume":"9","author":[{"given":"Lianyi","family":"Han","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanli","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen H","family":"Bryant","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2008,9,25]]},"reference":[{"issue":"1","key":"2386_CR1","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1016\/S1367-5931(97)80111-1","volume":"1","author":"JJ Burbaum","year":"1997","unstructured":"Burbaum JJ, Sigal NH: New technologies for high-throughput screening. 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