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1.
Unsupervised and supervised AI on molecular dynamics simulations reveals complex characteristics of HLA-A2-peptide immunogenicity.
Brief Bioinform
; 25(1)2023 11 22.
Article
in English
| MEDLINE | ID: mdl-38233090
2.
Analysis of Training and Seed Bias in Small Molecules Generated with a Conditional Graph-Based Variational AutoencoderâInsights for Practical AI-Driven Molecule Generation.
J Chem Inf Model
; 62(4): 801-816, 2022 02 28.
Article
in English
| MEDLINE | ID: mdl-35130440
3.
Active Site Sequence Representations of Human Kinases Outperform Full Sequence Representations for Affinity Prediction and Inhibitor Generation: 3D Effects in a 1D Model.
J Chem Inf Model
; 62(2): 240-257, 2022 01 24.
Article
in English
| MEDLINE | ID: mdl-34905358
4.
On the Choice of Active Site Sequences for Kinase-Ligand Affinity Prediction.
J Chem Inf Model
; 62(18): 4295-4299, 2022 09 26.
Article
in English
| MEDLINE | ID: mdl-36098536
5.
Simplified, interpretable graph convolutional neural networks for small molecule activity prediction.
J Comput Aided Mol Des
; 36(5): 391-404, 2022 05.
Article
in English
| MEDLINE | ID: mdl-34817762
6.
Combining Docking Pose Rank and Structure with Deep Learning Improves Protein-Ligand Binding Mode Prediction over a Baseline Docking Approach.
J Chem Inf Model
; 60(9): 4170-4179, 2020 09 28.
Article
in English
| MEDLINE | ID: mdl-32077698
7.
Role of chronic toxicology studies in revealing new toxicities.
Regul Toxicol Pharmacol
; 82: 94-98, 2016 Dec.
Article
in English
| MEDLINE | ID: mdl-27769827
8.
CACHE (Critical Assessment of Computational Hit-finding Experiments): A public-private partnership benchmarking initiative to enable the development of computational methods for hit-finding.
Nat Rev Chem
; 6(4): 287-295, 2022 Apr.
Article
in English
| MEDLINE | ID: mdl-35783295
9.
Drug-like density: a method of quantifying the "bindability" of a protein target based on a very large set of pockets and drug-like ligands from the Protein Data Bank.
J Chem Inf Model
; 50(11): 2029-40, 2010 Nov 22.
Article
in English
| MEDLINE | ID: mdl-20977231
10.
Developing timely insights into comparative effectiveness research with a text-mining pipeline.
Drug Discov Today
; 21(3): 473-80, 2016 Mar.
Article
in English
| MEDLINE | ID: mdl-26854423
11.
Application of an automated natural language processing (NLP) workflow to enable federated search of external biomedical content in drug discovery and development.
Drug Discov Today
; 21(5): 826-35, 2016 05.
Article
in English
| MEDLINE | ID: mdl-26979546
12.
Inhibitors of human histone deacetylase: synthesis and enzyme and cellular activity of straight chain hydroxamates.
J Med Chem
; 45(4): 753-7, 2002 Feb 14.
Article
in English
| MEDLINE | ID: mdl-11831887
13.
QSAR Prediction of Passive Permeability in the LLC-PK1 Cell Line: Trends in Molecular Properties and Cross-Prediction of Caco-2 Permeabilities.
Mol Inform
; 31(3-4): 231-45, 2012 Apr.
Article
in English
| MEDLINE | ID: mdl-27477094
14.
QSAR models for predicting the similarity in binding profiles for pairs of protein kinases and the variation of models between experimental data sets.
J Chem Inf Model
; 49(8): 1974-85, 2009 Aug.
Article
in English
| MEDLINE | ID: mdl-19639957
15.
Discovery of potent, selective, and orally active carboxylic acid based inhibitors of matrix metalloproteinase-13.
J Med Chem
; 52(11): 3523-38, 2009 Jun 11.
Article
in English
| MEDLINE | ID: mdl-19422229
16.
Multiple protein structures and multiple ligands: effects on the apparent goodness of virtual screening results.
J Comput Aided Mol Des
; 22(3-4): 257-65, 2008.
Article
in English
| MEDLINE | ID: mdl-18273559
17.
Comparison of topological, shape, and docking methods in virtual screening.
J Chem Inf Model
; 47(4): 1504-19, 2007.
Article
in English
| MEDLINE | ID: mdl-17591764
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