Impact of 2′-hydroxyl sampling on the conformational properties of RNA: Update of the CHARMM all-atom additive force field for RNA. - Elizabeth J. Denning; U. Deva Priyakumar; Lennart Nilsson; Alexander D. MacKerell Jr. (J. Comput. Chem., 2011)

Prediction of the structures of helical membrane proteins based on a minimum unfavorable contacts approach. - Siladitya Padhi; Siddabattula Ramakrishna; U. Deva Priyakumar (J. Comput. Chem., 2015)

Dynamics Based Pharmacophore Models for Screening Potential Inhibitors of Mycobacterial Cyclopropane Synthase. - Chinmayee Choudhury; U. Deva Priyakumar; G. Narahari Sastry (J. Chem. Inf. Model., 2015)

Chemically Interpretable Graph Interaction Network for Prediction of Pharmacokinetic Properties of Drug-Like Molecules. - Yashaswi Pathak; Siddhartha Laghuvarapu; Sarvesh Mehta; U. Deva Priyakumar (AAAI, 2020)

BAND NN: A Deep Learning Framework for Energy Prediction and Geometry Optimization of Organic Small Molecules. - Siddhartha Laghuvarapu; Yashaswi Pathak; U. Deva Priyakumar (J. Comput. Chem., 2020)

A Model of Graph Transactional Coverage Patterns with Applications to Drug Discovery. - A. Srinivas Reddy; P. Krishna Reddy; Anirban Mondal; U. Deva Priyakumar (HiPC, 2021)

MMBERT: Multimodal BERT Pretraining for Improved Medical VQA. - Yash Khare; Viraj Bagal; Minesh Mathew; Adithi Devi; U. Deva Priyakumar; C. V. Jawahar (ISBI, 2021)

Linear Prediction Residual for Efficient Diagnosis of Parkinson's Disease from Gait. - Shanmukh Alle; U. Deva Priyakumar (MICCAI (5), 2021)

IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification. - Likith Reddy; Vivek Talwar; Shanmukh Alle; Raju S. Bapi; U. Deva Priyakumar (SMC, 2021)

APObind: A Dataset of Ligand Unbound Protein Conformations for Machine Learning Applications in De Novo Drug Design. - Rishal Aggarwal; Akash Gupta 002; U. Deva Priyakumar (CoRR, 2021)

MoleGuLAR: Molecule Generation Using Reinforcement Learning with Alternating Rewards. - Manan Goel; Shampa Raghunathan; Siddhartha Laghuvarapu; U. Deva Priyakumar (J. Chem. Inf. Model., 2021)

Learning Atomic Interactions through Solvation Free Energy Prediction Using Graph Neural Networks. - Yashaswi Pathak; Sarvesh Mehta; U. Deva Priyakumar (J. Chem. Inf. Model., 2021)

Modified Variable Kernel Length ResNets for Heart Murmur Detection and Clinical Outcome Prediction Using Phonocardiogram Recordings. - Vijay Vignesh Venkataramani; Akshit Garg; U. Deva Priyakumar (CinC, 2022)

Modern AI/ML Methods for Healthcare: Opportunities and Challenges. - Akshit Garg; Vijay Vignesh Venkataramani; Akshaya Karthikeyan; U. Deva Priyakumar (ICDCIT, 2022)

Mining subgraph coverage patterns from graph transactions. - A. Srinivas Reddy; P. Krishna Reddy; Anirban Mondal; U. Deva Priyakumar (Int. J. Data Sci. Anal., 2022)

Benchmark study on deep neural network potentials for small organic molecules. - Rohit Modee; Siddhartha Laghuvarapu; U. Deva Priyakumar (J. Comput. Chem., 2022)

DeepPocket: Ligand Binding Site Detection and Segmentation using 3D Convolutional Neural Networks. - Rishal Aggarwal; Akash Gupta 002; Vineeth R. Chelur; C. V. Jawahar; U. Deva Priyakumar (J. Chem. Inf. Model., 2022)

MolGPT: Molecular Generation Using a Transformer-Decoder Model. - Viraj Bagal; Rishal Aggarwal; P. K. Vinod; U. Deva Priyakumar (J. Chem. Inf. Model., 2022)

BiRDS - Binding Residue Detection from Protein Sequences Using Deep ResNets. - Vineeth R. Chelur; U. Deva Priyakumar (J. Chem. Inf. Model., 2022)

A Machine Learning Approach for Outcome Prediction in Postanoxic Coma Patients Using Frequency Domain Features. - Vijay Vignesh Venkataramani; Akshit Garg; Maitreya Maity; U. Deva Priyakumar (CinC, 2023)

Single-Lead to Multi-Lead Electrocardiogram Reconstruction Using a Modified Attention U-Net Framework. - Akshit Garg; Vijay Vignesh Venkataramani; U. Deva Priyakumar (IJCNN, 2023)

Self-Supervision and Weak Supervision for Accurate and Interpretable Chest X-Ray Classification Models. - Abhiroop Talasila; Akshaya Karthikeyan; Shanmukh Alle; Maitreya Maity; U. Deva Priyakumar (IJCNN, 2023)

GraphDDI: Graph Neural Network for Prediction of Drug-Drug Interaction. - Suyash Gupta 003; Siddhartha Laghuvarapu; U. Deva Priyakumar (AIiH (1), 2024)

Self-Supervised Modality-Agnostic Pre-Training of Swin Transformers. - Abhiroop Talasila; Maitreya Maity; U. Deva Priyakumar (ISBI, 2024)

Deep reinforcement learning in chemistry: A review. - Bhuvanesh Sridharan; Animesh Sinha; Jai Bardhan; Rohit Modee; Masahiro Ehara; U. Deva Priyakumar (J. Comput. Chem., 2024)