Title |
Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs
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Published in |
BMC Bioinformatics, May 2012
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DOI | 10.1186/1471-2105-13-112 |
Pubmed ID | |
Authors |
Suleiman A Khan, Ali Faisal, John Patrick Mpindi, Juuso A Parkkinen, Tuomo Kalliokoski, Antti Poso, Olli P Kallioniemi, Krister Wennerberg, Samuel Kaski |
Abstract |
Detailed and systematic understanding of the biological effects of millions of available compounds on living cells is a significant challenge. As most compounds impact multiple targets and pathways, traditional methods for analyzing structure-function relationships are not comprehensive enough. Therefore more advanced integrative models are needed for predicting biological effects elicited by specific chemical features. As a step towards creating such computational links we developed a data-driven chemical systems biology approach to comprehensively study the relationship of 76 structural 3D-descriptors (VolSurf, chemical space) of 1159 drugs with the microarray gene expression responses (biological space) they elicited in three cancer cell lines. The analysis covering 11350 genes was based on data from the Connectivity Map. We decomposed the biological response profiles into components, each linked to a characteristic chemical descriptor profile. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Germany | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Scientists | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Portugal | 1 | 2% |
Netherlands | 1 | 2% |
Brazil | 1 | 2% |
India | 1 | 2% |
Belgium | 1 | 2% |
Unknown | 50 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 20 | 36% |
Student > Ph. D. Student | 11 | 20% |
Student > Master | 6 | 11% |
Other | 3 | 5% |
Professor > Associate Professor | 3 | 5% |
Other | 7 | 13% |
Unknown | 5 | 9% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 21 | 38% |
Computer Science | 11 | 20% |
Chemistry | 8 | 15% |
Biochemistry, Genetics and Molecular Biology | 5 | 9% |
Mathematics | 2 | 4% |
Other | 3 | 5% |
Unknown | 5 | 9% |