Combinatorial Chemistry & High Throughput Screening

Accelerated Technologies for Biotechnology, Bioassays, Medicinal Chemistry and Natural Products Research


Gerald H. Lushington
LiS Consulting, Lawrence

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Editorial [Hot Topic: Machine Learning for Virtual Screening (Part 1) (Guest Editor: Ovidiu Ivanciuc)] promotion: free to download

Volume:12   Issue: 4
Pp: 330-331
Ovidiu Ivanciuc
DOI: 10.2174/138620709788167999

Machine Learning in Virtual Screening

Volume:12   Issue: 4
Pp: 332-343
James L. Melville, Edmund K. Burke and Jonathan D. Hirst
DOI: 10.2174/138620709788167980

Comparative Analysis of Machine Learning Methods in Ligand-Based Virtual Screening of Large Compound Libraries

Volume:12   Issue: 4
Pp: 344-357
Xiao H. Ma, Jia Jia, Feng Zhu, Ying Xue, Ze R. Li and Yu Z. Chen
DOI: 10.2174/138620709788167944

Performance of Machine Learning Methods for Ligand-Based Virtual Screening

Volume:12   Issue: 4
Pp: 358-368
Dariusz Plewczynski, Stephane A.H. Spieser and Uwe Koch
DOI: 10.2174/138620709788167962

Virtual Screening for Cytochromes P450: Successes of Machine Learning Filters

Volume:12   Issue: 4
Pp: 369-382
Julien Burton, Ismail Ijjaali, Francois Petitet, Andre Michel and Daniel P. Vercauteren
DOI: 10.2174/138620709788167935

Scaffold-Hopping Potential of Fragment-Based De Novo Design: The Chances and Limits of Variation

Volume:12   Issue: 4
Pp: 383-396
Bjoern A. Krueger, Axel Dietrich, Karl-Heinz Baringhaus and Gisbert Schneider
DOI: 10.2174/138620709788167971

Virtual Screening with Support Vector Machines and Structure Kernels

Volume:12   Issue: 4
Pp: 409-423
Pierre Mahe and Jean-Philippe Vert
DOI: 10.2174/138620709788167926

Reverse Fingerprinting and Mutual Information-Based Activity Labeling and Scoring (MIBALS)

Volume:12   Issue: 4
Pp: 424-439
Chris Williams and Suzanne K. Schreyer
DOI: 10.2174/138620709788167953

Review on Lazy Learning Regressors and their Applications in QSAR

Volume:12   Issue: 4
Pp: 440-450
Abhijit J. Kulkarni, Valadi K. Jayaraman and Bhaskar D. Kulkarni
DOI: 10.2174/138620709788167908