A Connectionist Parser Aimed at Spoken Language. - Ajay N. Jain; Alex Waibel (IWPT, 1989)

Incremental Parsing by Modular Recurrent Connectionist Networks. - Ajay N. Jain; Alex Waibel (NIPS, 1989)

Robust connectionist parsing of spoken language. - Ajay N. Jain; Alexander H. Waibel (ICASSP, 1990)

JANUS: a speech-to-speech translation system using connectionist and symbolic processing strategies. - Alex Waibel; Ajay N. Jain; Arthur E. McNair; Hiroaki Saito 001; Alexander G. Hauptmann; Joe Tebelskis (ICASSP, 1991)

Generalization Performance in PARSEC - A Structured Connectionist Parsing Architecture. - Ajay N. Jain (NIPS, 1991)

JANUS: Speech-to-Speech Translation Using Connectionist and Non-Connectionist Techniques. - Alex Waibel; Ajay N. Jain; Arthur E. McNair; Joe Tebelskis; Louise Osterholtz; Hiroaki Saito 001; Otto Schmidbauer; Tilo Sloboda; Monika Woszczyna (NIPS, 1991)

Parsing Complex Sentences with Structured Connectionist Networks. - Ajay N. Jain (Neural Comput., 1991)

PARSEC: a structured connectionist parsing system for spoken language. - Ajay N. Jain; Alex Waibel; David S. Touretzky (ICASSP, 1992)

A Comparison of Dynamic Reposing and Tangent Distance for Drug Activity Prediction. - Thomas G. Dietterich; Ajay N. Jain; Richard H. Lathrop; Tomás Lozano-Pérez (NIPS, 1993)

Compass: A shape-based machine learning tool for drug design. - Ajay N. Jain; Thomas G. Dietterich; Richard H. Lathrop; David Chapman; Roger E. Critchlow Jr.; Barr E. Bauer; Teresa A. Webster; Tomás Lozano-Pérez (J. Comput. Aided Mol. Des., 1994)

Musk (Version 1). - David Chapman; Ajay N. Jain (UCI Machine Learning Repository, 1994)

Musk (Version 2). - David Chapman; Ajay N. Jain (UCI Machine Learning Repository, 1994)

Scoring noncovalent protein-ligand interactions: A continuous differentiable function tuned to compute binding affinities. - Ajay N. Jain (J. Comput. Aided Mol. Des., 1996)

Morphological similarity: A 3D molecular similarity method correlated with protein-ligand recognition. - Ajay N. Jain (J. Comput. Aided Mol. Des., 2000)

Deriving quantitative conclusions from microarray expression data. - Adam B. Olshen; Ajay N. Jain (Bioinform., 2002)

Statistical issues in the analysis of the array CGH data. - Jane Fridlyand; Antoine Snijders; Dan Pinkel; Donna Albertson; Ajay N. Jain (CSB, 2003)

Wavelet Transforms for the Analysis of Microarray Experiments. - Taku A. Tokuyasu; Donna Albertson; Dan Pinkel; Ajay N. Jain (CSB, 2003)

A deterministic motif finding algorithm with application to the human genome. - Lawrence S. Hon; Ajay N. Jain (Bioinform., 2006)

Pathway recognition and augmentation by computational analysis of microarray expression data. - Barbara A. Novak; Ajay N. Jain (Bioinform., 2006)

Surflex-Dock 2.1: Robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search. - Ajay N. Jain (J. Comput. Aided Mol. Des., 2007)

Effects of inductive bias on computational evaluations of ligand-based modeling and on drug discovery. - Ann E. Cleves; Ajay N. Jain (J. Comput. Aided Mol. Des., 2008)

Bias, reporting, and sharing: computational evaluations of docking methods. - Ajay N. Jain (J. Comput. Aided Mol. Des., 2008)

Recommendations for evaluation of computational methods. - Ajay N. Jain; Anthony Nicholls (J. Comput. Aided Mol. Des., 2008)

Customizing scoring functions for docking. - Tuan A. Pham 001; Ajay N. Jain (J. Comput. Aided Mol. Des., 2008)

Accurate and Interpretable Computational Modeling of Chemical Mutagenicity. - James J. Langham; Ajay N. Jain (J. Chem. Inf. Model., 2008)

Effects of protein conformation in docking: improved pose prediction through protein pocket adaptation. - Ajay N. Jain (J. Comput. Aided Mol. Des., 2009)

QMOD: physically meaningful QSAR. - Ajay N. Jain (J. Comput. Aided Mol. Des., 2010)

Does your model weigh the same as a Duck? - Ajay N. Jain; Ann E. Cleves (J. Comput. Aided Mol. Des., 2012)

Surflex-Dock: Docking benchmarks and real-world application. - Russell Spitzer; Ajay N. Jain (J. Comput. Aided Mol. Des., 2012)

A structure-guided approach for protein pocket modeling and affinity prediction. - Rocco Varela; Ann E. Cleves; Russell Spitzer; Ajay N. Jain (J. Comput. Aided Mol. Des., 2013)

Prediction of Off-Target Drug Effects Through Data Fusion. - Emmanuel R. Yera; Ann E. Cleves; Ajay N. Jain (Pacific Symposium on Biocomputing, 2014)

Surflex-QMOD: physically meaningful QSAR. - Alexander Steudle; Rocco Varela; Ajay N. Jain (J. Cheminformatics, 2014)

Chemical and protein structural basis for biological crosstalk between PPARα and COX enzymes. - Ann E. Cleves; Ajay N. Jain (J. Comput. Aided Mol. Des., 2015)

Knowledge-guided docking: accurate prospective prediction of bound configurations of novel ligands using Surflex-Dock. - Ann E. Cleves; Ajay N. Jain (J. Comput. Aided Mol. Des., 2015)

Extrapolative prediction using physically-based QSAR. - Ann E. Cleves; Ajay N. Jain (J. Comput. Aided Mol. Des., 2016)

ForceGen 3D structure and conformer generation: from small lead-like molecules to macrocyclic drugs. - Ann E. Cleves; Ajay N. Jain (J. Comput. Aided Mol. Des., 2017)

Quantitative surface field analysis: learning causal models to predict ligand binding affinity and pose. - Ann E. Cleves; Ajay N. Jain (J. Comput. Aided Mol. Des., 2018)

Electrostatic-field and surface-shape similarity for virtual screening and pose prediction. - Ann E. Cleves; Stephen R. Johnson; Ajay N. Jain (J. Comput. Aided Mol. Des., 2019)

Complex macrocycle exploration: parallel, heuristic, and constraint-based conformer generation using ForceGen. - Ajay N. Jain; Ann E. Cleves; Qi Gao; Xiao Wang; Yizhou Liu; Edward C. Sherer; Mikhail Y. Reibarkh (J. Comput. Aided Mol. Des., 2019)

Structure- and Ligand-Based Virtual Screening on DUD-E+: Performance Dependence on Approximations to the Binding Pocket. - Ann E. Cleves; Ajay N. Jain (J. Chem. Inf. Model., 2020)

Synergy and Complementarity between Focused Machine Learning and Physics-Based Simulation in Affinity Prediction. - Ann E. Cleves; Stephen R. Johnson; Ajay N. Jain (J. Chem. Inf. Model., 2021)

Complex peptide macrocycle optimization: combining NMR restraints with conformational analysis to guide structure-based and ligand-based design. - Ajay N. Jain; Alexander C. Brueckner; Christine Jorge; Ann E. Cleves; Purnima Khandelwal; Janet Caceres Cortes; Luciano Mueller (J. Comput. Aided Mol. Des., 2023)

Deep-Learning Based Docking Methods: Fair Comparisons to Conventional Docking Workflows. - Ajay N. Jain; Ann E. Cleves; W. Patrick Walters (CoRR, 2024)

PARSEC: A Connectionist Learning Architecture for Parsing Spoken Language - Ajay N. Jain (2024)

From UK-2A to florylpicoxamid: Active learning to identify a mimic of a macrocyclic natural product. - Ann E. Cleves; Ajay N. Jain; David A. Demeter; Zachary A. Buchan; Jeremy Wilmot; Erin N. Hancock (J. Comput. Aided Mol. Des., 2024)

Structure-based pose prediction: Non-cognate docking extended to macrocyclic ligands. - Ann E. Cleves; Himani Tandon; Ajay N. Jain (J. Comput. Aided Mol. Des., 2024)

Correction: Complex peptide macrocycle optimization: combining NMR restraints with conformational analysis to guide structure-based and ligand-based design. - Ajay N. Jain; Alexander C. Brueckner; Christine Jorge; Ann E. Cleves; Purnima Khandelwal; Janet Caceres Cortes; Luciano Mueller (J. Comput. Aided Mol. Des., 2024)