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231223s2010 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.21347
|2 doi
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|a pubmed25n0632.xml
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|a DE-627
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|e rakwb
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|a eng
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| 100 |
1 |
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|a Rao, Hanbing
|e verfasserin
|4 aut
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| 245 |
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|a Identification of small molecule aggregators from large compound libraries by support vector machines
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|c 2010
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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|a Date Completed 16.04.2010
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|a Date Revised 03.02.2010
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|a published: Print
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|a Citation Status MEDLINE
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|a (c) 2009 Wiley Periodicals, Inc.
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|a Small molecule aggregators non-specifically inhibit multiple unrelated proteins, rendering them therapeutically useless. They frequently appear as false hits and thus need to be eliminated in high-throughput screening campaigns. Computational methods have been explored for identifying aggregators, which have not been tested in screening large compound libraries. We used 1319 aggregators and 128,325 non-aggregators to develop a support vector machines (SVM) aggregator identification model, which was tested by four methods. The first is five fold cross-validation, which showed comparable aggregator and significantly improved non-aggregator identification rates against earlier studies. The second is the independent test of 17 aggregators discovered independently from the training aggregators, 71% of which were correctly identified. The third is retrospective screening of 13M PUBCHEM and 168K MDDR compounds, which predicted 97.9% and 98.7% of the PUBCHEM and MDDR compounds as non-aggregators. The fourth is retrospective screening of 5527 MDDR compounds similar to the known aggregators, 1.14% of which were predicted as aggregators. SVM showed slightly better overall performance against two other machine learning methods based on five fold cross-validation studies of the same settings. Molecular features of aggregation, extracted by a feature selection method, are consistent with published profiles. SVM showed substantial capability in identifying aggregators from large libraries at low false-hit rates
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|a Journal Article
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| 650 |
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|a Small Molecule Libraries
|2 NLM
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| 700 |
1 |
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|a Li, Zerong
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Li, Xiangyuan
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Ma, Xiaohua
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Ung, Choongyong
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Li, Hu
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Liu, Xianghui
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Chen, Yuzong
|e verfasserin
|4 aut
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| 773 |
0 |
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|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 31(2010), 4 vom: 01. März, Seite 752-63
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnas
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| 773 |
1 |
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|g volume:31
|g year:2010
|g number:4
|g day:01
|g month:03
|g pages:752-63
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| 856 |
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|u http://dx.doi.org/10.1002/jcc.21347
|3 Volltext
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