Sao Carlos, Brazil, 9-13 November 2014
Drug Design 2014
Oxford, UK, 23-25 September 2014
Edinburgh, UK, 7-10 September 2014
SCI Symposium Efficient Methods for Hit ID 2014
London, UK, 11 June 2014
7th Global Discovery & Development Innovation Forum
London, UK, 13/14 May 2014
Europe Drug Discovery Summit
Berlin, Germany, 7/8 May 2014
Informa Drug Discovery Innovations
Berlin, Germany, 18/19 March 2014
SLAS (Society for Laboratory Automation & Screening) 2014
San Diego, California/US, 18-22 January 2014
Chemical Biology and Drug Discovery Programme 2014
Mysore, India, 9/10 January 2014
Computational Tools for Chemical Biology, Phenotypic Screening and Target De-convolution
Hinxton, UK, 22 November 2013
15th Cefic-LRI Annual Workshop 2013
Brussels, Belgium, 21 November 2013
Shah Alam, Malaysia, 4/5 September 2013
eSSENCE International Workshop on Macromolecular Structure and Dynamics
Uppsala, Sweden, 3-5 June 2013
Informa Drug Discovery Innovations
Berlin, Germany, 19/20 March 2013
Advances and Progress in Drug Design
London, UK, 18-19 February 2013
UiTM Academic Conference 2013
Kuala Lumpur, Malaysia, 29-30 January 2013
German Cheminformatics Conference 2012
Goslar, Germany, 11-13 November 2012
Basle, Switzerland, 24-27 September 2012
Symposium on Computational Chemical Biology
Manchester, UK, 13 September 2012
22nd International Symposium on Medicinal Chemistry (EFMC-ISMC 2012)
Berlin, Germany, 2-6 September 2012
2012 Sino-American Symposium on Clinical and Translational Medicine (SAS-CTM)
Shanghai, China, 27-29 June 2012
SocBIN Bioinformatics 2012
Stockholm, Sweden, 11-14 June 2012
Good Practice in Traditional Chinese Medicine (GP-TCM)
Leiden, The Netherlands, 15-18 April 2012
RIKEN Chemical Biology Symposium
Wako, Japan, 20-21 October 2011
47th International Conference on Medicinal Chemistry (Plenary Lecture)
Lyon, France, 6-8 July 2011
Frontiers in Medicinal Chemistry 2011
Saarbruecken, Germany, 20-23 March 2011
Global Discovery & Development Innovation Forum 2011
London, U. K., 7-8 March 2011
World Drug Discovery & Development Summit 2010
Copenhagen, Denmark, 26-27 October 2010
XIXth LACDR School on Medicinal Chemistry
Oegstgeest, The Netherlands, 19-22 October 2010
UK QSAR Meeting Fall 2010
Cambridge, UK, 12 October 2010
FIGON Dutch Medicines Days 2010
Lunteren, The Netherlands, 4-6 October 2010
21st International Symposium on Medicinal Chemistry
Brussels, Belgium, 5-9 September 2010
Second Strasbourg Summer School on Chemoinformatics
Obernai, France, 20-24 June 2010
Bio-IT World 2010
Boston/MA, 20-22 April 2010
British Toxicology Society Annual Meeting 2010
Edinburgh, 28-31 March 2010
In silico discovery of molecular probes and drug-like compounds: Success & Challenges
Ile de France, France, 23-25 March 2010
Fragment-Based Lead Design 2009
York/UK, 20-23 September 2009
Cochin/India, 19-21 August 2009
Bio-IT World Conference & Expo
Boston/USA, 27-29 April 2009
Addis Ababa University
Addis Ababa/Ethiopia, 9 January 2009
Basel/Switzerland, 14-16 October 2008
Virtual Discovery Europe
Amsterdam/The Netherlands, 19-20 June 2008
8th International Conference on Chemical Structures
Noordwijkerhout/The Netherlands, 1-5 June 2008
Bio-IT World Conference & Expo
Boston/USA, 28-30 April 2008
6th Annual Congress: G Protein-Coupled Receptors in Drug Discovery
Berlin/Germany, 10-13 March 2008
Recent publications (More Publications)
| 113. Biofragments: an approach towards predicting protein function using biologically-related fragments, and its application to Mycobacterium tuberculosis CYP126.|
Sean A. Hudson, et al., ChemBioChem. 2014 (in press).
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| 112. How Diverse Are Diversity Assessment Methods? A Comparative Analysis and Benchmarking of Molecular Descriptor Space.|
Alexios Koutsoukas, et al., J. Chem. Inf. Model. 2014 (in press).
| 111. Synthesis and biological evaluation of tetrahydropyridinepyrazoles ('PFPs') as inhibitors of STAT3 phosphorylation.|
Revanna C. N., et al., MedChemComm 2014 (5) 32 - 40.
| 110. Predicting Toxic Effects of Metabolites.|
Andreas Bender, In: Drug Metabolism Prediction. Johannes Kirchmair (Ed.), Wiley, New York 2014.
| 109. Are phylogenetic trees suitable for chemogenomics analyses of bioactivity data sets: the importance of shared active compounds and choosing a suitable data embedding method, as exemplified on Kinases.|
Shardul Paricharak, et al., J. Cheminf. 2013 (5) 49.
| 108. Evaluation of antioxidant and antimicrobial activities of the phenolic composition of Algerian Arbutus unedo L. Roots.|
Nassim Djabou, et al., Pharmacognosy J. 2013 (5) 275 - 280.
|107. Experimental Confirmation of New Drug-Target Interactions Predicted by Drug Profile Matching.|
Laszlo Vegner, et al., J. Med. Chem. 2013 (56) 8377 - 8388.
|106. Design, Synthesis, and Biological Evaluation of an Allosteric Inhibitor of HSET that Targets Cancer Cells with Supernumerary Centrosomes.|
Ciorsdaidh A. Watts, et al., Chem. Biol. 2013 (20) 1399 - 1410.
|105. Benchmarking of protein descriptor sets in proteochemometric modeling (part 2): modeling performance of 13 amino acid descriptor sets.|
Gerard J. P. van Westen, et al., J. Cheminf. 2013 (5) 42.
|104. Benchmarking of protein descriptor sets in proteochemometric modeling (part 1): comparative study of 13 amino acid descriptor sets.|
Gerard J. P. van Westen, et al., J. Cheminf. 2013 (5) 41.
|103. Extensions to In Silico Bioactivity Predictions Using Pathway Annotations and Differential Pharmacology Analysis: Application to Xenopus laevis Phenotypic Readouts.|
Sonia Liggi, et al., Mol. Inf. 2013 (11-12) 1009 - 1024.
|102. In silico target predictions: defining a benchmarking dataset and comparison of performance of the multiclass NaÔve Bayes and Parzen-Rosenblatt Window.|
Alexios Koutsoukas, et al., J. Chem. Inf. Model. 2013 (53) 1957 - 1966.
|101. Linking Ayurveda and Western Medicine by Integrative Analysis.|
Fazlin Mohd-Fauzi, et al., J. Ayurveda Integr. Med. 2013 (4) 117 - 119.
|100. Diversity selection of compounds based on 'Protein Affinity Fingerprints' improves sampling of bioactive chemical space.|
Ha P. Nguyen, et al., Chem. Biol. Drug Des. 2013 (82) 252 - 266.
|99. Computer-Aided ('In silico') Approaches in the Mode-of-Action Analysis and Safety Assessment of Ostarine and 4-Methylamphetamine.|
Fazlin Mohd-Fauzi, et al., Human Psycopharmacol. 2013 (28) 365 - 378.
|98. Significantly Improved HIV Inhibitor Efficacy Prediction Employing Proteochemometric Models Generated From Antivirogram Data.|
Gerard J. P. van Westen, et al., PLoS Comp. Biol. 2013 (9) e1002899.
|97. Chemogenomics Approaches to Rationalizing the Mode-of-Action of Traditional Chinese and Ayurvedic Medicines.|
Fazlin Mohd Fauzi, et al., J. Chem. Inf. Model. 2013 (53) 661 - 673.
|96. Experimental Validation of In Silico Target Predictions on Synergistic Protein Targets.|
Isidro Cortes-Ciriano, et al., MedChemComm 2013 (4) 278 - 288.
|95. Identifying Novel Adenosine Receptor Ligands by Simultaneous Proteochemometric Modeling of Rat and Human Bioactivity Data.|
Gerard J. P. van Westen, et al., J. Med Chem. 2012 (55) 7010 - 7020.
|94. A Two-Directional Strategy for the Diversity-Oriented Synthesis of Macrocyclic Scaffolds.|
Kieron O'Connell, et al., Org. Biomol. Chem. 2012 (10) 7545 - 7551.
|93. Using multiobjective optimization and energy minimization to design an isoform-selective ligand of the 14-3-3 protein.|
Hernando Sanchez-Faddeev, et al., Lect. Notes. Comput. Sci. 2012 (7610) 12 - 24.
|92. Multi-Objective Evolutionary Design of Adenosine Receptor Ligands.|
Eelke van der Horst, et al., J. Chem. Inf. Model. 2012 (52) 1713 - 1721.
|91. Predicting Genes Involved in Human Cancer Using Network Contextual Information.|
Hossein Rahmani, et al., J. Integr. Bioinf. 2012 (9) 210.
|90. A Prospective Cross-Screening Study on G Protein-Coupled Receptors: Lessons Learned in Virtual Compound Library Design.|
Marijn P. A. Sanders, et al., J. Med Chem. 2012 (55) 5311 - 5325.
Joerg K. Wegner, et al., Comm. ACM 2012 (55) 65 - 75.
|88. Recognizing Pitfalls in Virtual Screening: A Critical Review.|
Thomas Scior, et al., J. Chem. Inf. Model. 2012 (52) 867 - 881.
|87. A-Ring Dihalogenation Increases the Cellular Activity of Combretastatin-Templated Tetrazoles.|
Thomas M. Beale, et al., ACS Med. Chem. Lett 2012 (3) 177 - 181.
|86. Computational Prediction of Metabolism: Sites, Products, SAR, P450 Enzyme Dynamics, and Mechanisms.|
Johannes Kirchmair, et al., J. Chem. Inf. Model. 2012 (52) 617 - 648.
|85. The challenges involved in Modeling Toxicity Data in silico: A Review.|
M. Paul Gleeson, et al., Curr. Pharm. Des. 2012 (18) 1266 - 1291.