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SVM-Based Feature Selection for Characterization of Focused Compound Collections
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/(sici)1521-3773(19991004)38:19<2894::aid-anie2894>3.0.co;2-fopenalex-snapshot
“Scaffold-Hopping” by Topological Pharmacophore Search: A Contribution to Virtual Screening
inferredcites →https://doi.org/10.1002/(sici)1521-3773(19991004)38:19<2896::aid-anie2896>3.0.co;2-3openalex-snapshot
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inferredcites →https://doi.org/10.1002/qsar.200330825openalex-snapshot
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inferredcites →https://doi.org/10.1016/0005-2795(75)90109-9openalex-snapshot
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inferredcites →https://doi.org/10.1016/0009-2614(82)80009-2openalex-snapshot
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inferredcites →https://doi.org/10.1016/0378-3758(90)90051-uopenalex-snapshot
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inferredcites →https://doi.org/10.1016/0898-5529(90)90156-3openalex-snapshot
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inferredcites →https://doi.org/10.1016/s0004-3702(97)00043-xopenalex-snapshot
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inferredcites →https://doi.org/10.1016/s0960-894x(99)00582-xopenalex-snapshot
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inferredcites →https://doi.org/10.1016/s1093-3263(00)00063-2openalex-snapshot
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inferredcites →https://doi.org/10.1017/cbo9780511801389openalex-snapshot
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inferredcites →https://doi.org/10.1021/ci00008a012openalex-snapshot
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inferredcites →https://doi.org/10.1021/ci0341161openalex-snapshot
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inferredcites →https://doi.org/10.1023/a:1012487302797openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/9780470048672.wecb072openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/9780470116449.ch6openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/ange.201909987openalex-snapshot
Autonome Entdeckung in den chemischen Wissenschaften, Teil I: Fortschritt
inferred← citeshttps://doi.org/10.1002/anie.201909987openalex-snapshot
Autonomous Discovery in the Chemical Sciences Part I: Progress
inferred← citeshttps://doi.org/10.1002/cbic.200400400openalex-snapshot
From Virtual to Real Screening for D3 Dopamine Receptor Ligands
inferred← citeshttps://doi.org/10.1002/jcc.20831openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/minf.201000096openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/minf.201100059openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/qsar.200420056openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/qsar.200510120openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/qsar.200610078openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/qsar.200630143openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/11560500_16openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-09153-6_3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-540-30478-4_17openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-540-36266-1_10openalex-snapshot
Advances in the Application of Machine Learning Techniques in Drug Discovery, Design and Development
inferred← citeshttps://doi.org/10.1007/978-3-642-53917-6_17openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10822-005-3785-3openalex-snapshot
A support vector machine approach to classify human cytochrome P450 3A4 inhibitors
inferred← citeshttps://doi.org/10.1007/s11030-005-6293-4openalex-snapshot
Multi-space classification for predicting GPCR-ligands
inferred← citeshttps://doi.org/10.1007/springerreference_302011openalex-snapshot
Mean-Field Theory of Meta-learning
inferred← citeshttps://doi.org/10.1016/b978-0-08-100098-4.00007-7openalex-snapshot
In Silico ADMET Profiling
inferred← citeshttps://doi.org/10.1016/j.chemolab.2010.06.008openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.ejmech.2011.05.031openalex-snapshot
Combined SVM-based and docking-based virtual screening for retrieving novel inhibitors of c-Met
inferred← citeshttps://doi.org/10.1016/j.jmgm.2008.08.004openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jtbi.2004.11.031openalex-snapshot
Directed molecular evolution by machine learning and the influence of nonlinear interactions
inferred← citeshttps://doi.org/10.1016/j.jtbi.2014.04.021openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/s1574-1400(06)02008-1openalex-snapshot
Chapter 8 Machine Learning in Computational Chemistry
inferred← citeshttps://doi.org/10.1021/acs.jcim.5b00722openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci0600915openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci1001394openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci200311wopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci6002619openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci7003253openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/jm050619hopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/jm800504qopenalex-snapshot
In SilicoFunctional Profiling of Small Molecules and Its Applications
inferred← citeshttps://doi.org/10.1021/pr8002886openalex-snapshot
The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events
inferred← citeshttps://doi.org/10.1038/srep36595openalex-snapshot
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inferred← citeshttps://doi.org/10.1088/1742-5468/2009/11/p11003openalex-snapshot
Mean-field theory of meta-learning
inferred← citeshttps://doi.org/10.1093/nar/gkl583openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/bcd.2019.8885219openalex-snapshot
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inferred← citeshttps://doi.org/10.1111/j.1747-0285.2006.00379.xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1186/1471-2105-5-135openalex-snapshot
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inferred← citeshttps://doi.org/10.1201/b19853-2openalex-snapshot
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inferred← citeshttps://doi.org/10.1201/b19853-7openalex-snapshot
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inferred← citeshttps://doi.org/10.1517/17460441.2014.866943openalex-snapshot
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inferred← citeshttps://doi.org/10.2174/092986712800167356openalex-snapshot
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inferred← citeshttps://doi.org/10.31925/farmacia.2022.2.17openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fchem.2018.00082openalex-snapshot
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inferred← citeshttps://doi.org/10.34040/ijcb.1.1.2012.12openalex-snapshot
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inferred← citeshttps://doi.org/10.34040/ijcb.1.1.2012.20openalex-snapshot
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inferred← citeshttps://doi.org/10.4018/978-1-4666-2542-6.ch013openalex-snapshot
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inferred← citeshttps://doi.org/10.4018/978-1-4666-3604-0.ch040openalex-snapshot
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inferred← citeshttps://doi.org/10.4018/978-1-61520-911-8.ch002openalex-snapshot
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inferred← citeshttps://doi.org/10.4137/becb.s7503openalex-snapshot
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inferred← citeshttps://doi.org/10.5109/2203031openalex-snapshot
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inferred← citeshttps://doi.org/10.5740/jaoacint.sge_goodarziopenalex-snapshot
Feature Selection Methods in QSAR Studies
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