Chemical data mining of the NCI human tumor cell line database.
Identifieur interne : 000036 ( Ncbi/Merge ); précédent : 000035; suivant : 000037Chemical data mining of the NCI human tumor cell line database.
Auteurs : Huijun Wang [États-Unis] ; Jonathan Klinginsmith ; Xiao Dong ; Adam C. Lee ; Rajarshi Guha ; Yuqing Wu ; Gordon M. Crippen ; David J. WildSource :
- Journal of chemical information and modeling [ 1549-9596 ]
Descripteurs français
- Wicri :
- geographic : États-Unis.
English descriptors
- KwdEn :
- Antineoplastic Agents (chemistry), Antineoplastic Agents (pharmacology), Cell Line, Tumor, Cell Proliferation (drug effects), Databases, Factual, Drug Evaluation, Preclinical, Gene Expression Regulation, Neoplastic (drug effects), Humans, Molecular Structure, National Cancer Institute (U.S.), Neoplasms (pathology), United States.
- MESH :
- chemical , chemistry : Antineoplastic Agents.
- chemical , pharmacology : Antineoplastic Agents.
- geographic : United States.
- drug effects : Cell Proliferation, Gene Expression Regulation, Neoplastic.
- pathology : Neoplasms.
- Cell Line, Tumor, Databases, Factual, Drug Evaluation, Preclinical, Humans, Molecular Structure, National Cancer Institute (U.S.).
Abstract
The NCI Developmental Therapeutics Program Human Tumor cell line data set is a publicly available database that contains cellular assay screening data for over 40 000 compounds tested in 60 human tumor cell lines. The database also contains microarray assay gene expression data for the cell lines, and so it provides an excellent information resource particularly for testing data mining methods that bridge chemical, biological, and genomic information. In this paper we describe a formal knowledge discovery approach to characterizing and data mining this set and report the results of some of our initial experiments in mining the set from a chemoinformatics perspective.
DOI: 10.1021/ci700141x
PubMed: 17915856
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pubmed:17915856Le document en format XML
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<front><div type="abstract" xml:lang="en">The NCI Developmental Therapeutics Program Human Tumor cell line data set is a publicly available database that contains cellular assay screening data for over 40 000 compounds tested in 60 human tumor cell lines. The database also contains microarray assay gene expression data for the cell lines, and so it provides an excellent information resource particularly for testing data mining methods that bridge chemical, biological, and genomic information. In this paper we describe a formal knowledge discovery approach to characterizing and data mining this set and report the results of some of our initial experiments in mining the set from a chemoinformatics perspective.</div>
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