Active Learning for drug discovery

[1]  Egon L. Willighagen,et al.  Bioclipse-R: integrating management and visualization of life science data with statistical analysis , 2013, Bioinform..

[2]  Emilio Benfenati,et al.  Simplified Molecular Input Line Entry System‐Based Optimal Descriptors: Quantitative Structure–Activity Relationship Modeling Mutagenicity of Nitrated Polycyclic Aromatic Hydrocarbons , 2009, Chemical biology & drug design.

[3]  John M. Barnard,et al.  Chemical Similarity Searching , 1998, J. Chem. Inf. Comput. Sci..

[4]  Jörg Huwyler,et al.  Computational Prediction of Blood-Brain Barrier Permeability Using Decision Tree Induction , 2012, Molecules.

[5]  Ian H. Gilbert,et al.  N-Myristoyltransferase inhibitors as new leads to treat sleeping sickness , 2010, Nature.

[6]  Bruce R Donald,et al.  Phylogenetic Classification of Protozoa Based on the Structure of the Linker Domain in the Bifunctional Enzyme, Dihydrofolate Reductase-Thymidylate Synthase* , 2003, Journal of Biological Chemistry.

[7]  M. Davey,et al.  Drug resistance mechanisms in helminths: is it survival of the fittest? , 2009, Trends in parasitology.

[8]  C. Lipinski The anti-intellectual effects of intellectual property. , 2006, Current opinion in chemical biology.

[9]  Andrew W. Moore,et al.  Active Learning for Anomaly and Rare-Category Detection , 2004, NIPS.

[10]  M. Boguski,et al.  Repurposing with a Difference , 2009, Science.

[11]  Igor V Tetko,et al.  Computing chemistry on the web. , 2005, Drug discovery today.

[12]  Gunnar Rätsch,et al.  Active Learning in the Drug Discovery Process , 2001, NIPS.

[13]  Peter E. Hart,et al.  Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.

[14]  Ross D. King,et al.  Yeast-based automated high-throughput screens to identify anti-parasitic lead compounds , 2013, Open Biology.

[15]  Igor V. Tetko,et al.  Virtual Computational Chemistry Laboratory – Design and Description , 2005, J. Comput. Aided Mol. Des..

[16]  K. Silamut,et al.  Artemisinin resistance in Plasmodium falciparum malaria. , 2009, The New England journal of medicine.

[17]  Christopher H. Bryant,et al.  Functional genomic hypothesis generation and experimentation by a robot scientist , 2004, Nature.

[18]  Maria Liakata,et al.  Towards Robot Scientists for autonomous scientific discovery , 2010, Automated experimentation.

[19]  J. A. Baranauskas,et al.  Prediction of Antimicrobial Activity of Synthetic Peptides by a Decision Tree Model , 2013, Applied and Environmental Microbiology.

[20]  D. Mabey,et al.  Neglected tropical diseases. , 2010, British medical bulletin.

[21]  Burr Settles,et al.  Active Learning Literature Survey , 2009 .

[22]  Ross D. King,et al.  Functional Expression of Parasite Drug Targets and Their Human Orthologs in Yeast , 2011, PLoS neglected tropical diseases.

[23]  M. Moran GLOBAL FUNDING OF NEW PRODUCTS FOR NEGLECTED TROPICAL DISEASES , 2011 .

[24]  M. C. Jones,et al.  Statistical Modelling Using Genstat , 1999 .

[25]  P J Goodford,et al.  Drug design by the method of receptor fit. , 1984, Journal of medicinal chemistry.

[26]  Bernard F. Buxton,et al.  Drug Design by Machine Learning: Support Vector Machines for Pharmaceutical Data Analysis , 2001, Comput. Chem..

[27]  Qing-Song Xu,et al.  Support vector machines and its applications in chemistry , 2009 .

[28]  D. Dennis,et al.  SDO : A Statistical Method for Global Optimization , 1997 .

[29]  N. Null The IUPAC International Chemical Identifier (InChI) , 2009 .

[30]  Luc De Raedt,et al.  Active Learning for High Throughput Screening , 2008, Discovery Science.

[31]  Gunnar Rätsch,et al.  Active Learning with Support Vector Machines in the Drug Discovery Process , 2003, J. Chem. Inf. Comput. Sci..

[32]  J. Drews Drug discovery: a historical perspective. , 2000, Science.

[33]  Michael J. Keiser,et al.  Predicting new molecular targets for known drugs , 2009, Nature.

[34]  Sanjoy Dasgupta,et al.  Hierarchical sampling for active learning , 2008, ICML '08.

[35]  Tomasz Arodz and Arkadiusz Z. Dudek Multivariate Modeling and Analysis in Drug Discovery , 2007 .

[36]  Joel S. Freundlich,et al.  The fatty acid biosynthesis enzyme FabI plays a key role in the development of liver-stage malarial parasites. , 2008, Cell host & microbe.

[37]  Rich Caruana,et al.  Multitask Learning , 1997, Machine Learning.

[38]  Andrey A. Toropov,et al.  Prediction of Aquatic Toxicity: Use of Optimization of Correlation Weights of Local Graph Invariants , 2003, J. Chem. Inf. Comput. Sci..

[39]  Jahan B. Ghasemi,et al.  Molecular docking and 3D-QSAR studies of falcipain inhibitors using CoMFA, CoMSIA, and Open3DQSAR , 2011, Medicinal Chemistry Research.

[40]  Joel Lexchin,et al.  The cost of drug development: a systematic review. , 2011, Health policy.

[41]  Jonathan D. Hirst,et al.  Similarity by Compression , 2007, J. Chem. Inf. Model..

[42]  Ethem Alpaydin,et al.  Introduction to machine learning , 2004, Adaptive computation and machine learning.

[43]  Donald R. Jones,et al.  Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..

[44]  Egon L. Willighagen,et al.  Bioclipse 2: A scriptable integration platform for the life sciences , 2009, BMC Bioinformatics.

[45]  S. Levy,et al.  Triclosan targets lipid synthesis , 1998, Nature.

[46]  Sandra D. Melman,et al.  Reduced Susceptibility to Praziquantel among Naturally Occurring Kenyan Isolates of Schistosoma mansoni , 2009, PLoS neglected tropical diseases.