S Mehta, S Laghuvarapu, Y Pathak, A Sethi, M Alvala, UD Priyakumar -
Machine Learning framework for enhanced molecular screening ,
Chemical Science 12 (35), 11710-11721
M Goel, S Raghunathan, S Laghuvarapu, UD Priyakumar - MoleGuLAR: Molecule Generation using Reinforcement Learning with Alternating Rewards , J. Chem. Inf. Model. 2021, 61, 12, 5815–5826
R Aggarwal, A Gupta, UD Priyakumar - APObind: A Dataset of Ligand Unbound Protein Conformations for Machine Learning Applications in De Novo Drug Design , arXiv, 2021
Moolamalla STR, Balasubramanian R, Chauhan R, Priyakumar UD, Vinod PK - Host metabolic reprogramming in response to SARS-CoV-2 infection: A systems biology approach , Microbial Pathogenesis 158, 105114
P Mehta, S Alle, A Chaturvedi, A Swaminathan, S Saifi, R Maurya, P Chattopadhyay, P Devi, R Chauhan, A Kanakan, JS Vasudevan, R Sethuraman, S Chidambaram, M Srivastava, A Chakravarthi, J Jacob, M Namagiri, V Konala, S Jha, UD Priyakumar, PK Vinod, R Pandey - Clinico-Genomic Analysis Reveals Mutations Associated with COVID-19 Disease Severity: Possible Modulation by RNA Structure , Pathogens 2021
S Alle, UD Priyakumar - Linear Prediction Residual for Efficient Diagnostics of Parkinson’s Disease from Gait, MICCAI 2021
V Bagal, R Aggarwal , PK Vinod, UD Priyakumar - MolGPT: Molecular Generation Using a Transformer – Decoder Model, Journal of Chemical Information and Modeling
Chauhan R, Vinod PK and Jawahar CV - Exploring genetic-histologic relationships in breast cancer , IEEE International Symposium on Biomedical Imaging (ISBI)
A Shukla, RS Bapi -
Numerical Magnitude Affects Accuracy but Not Precision of Temporal Judgments ,
Frontiers in Human Neuroscience
K Bera, A Shukla, RS Bapi -
Motor Chunking in Internally Guided Sequencing ,
Brain Sciences
K Bera, A Shukla, RS Bapi -
Learning Behaviors involved in Internally-Guided Motor Skill Learning ,
Frontiers in Psychology
YS BL, S Raghunathan, UD Priyakumar -
SCONES: Self-Consistent Neural Network for Protein Stability Prediction Upon Mutation ,
R Modee, S Agarwal, A Verma, K Joshi, UD Priyakumar -
DART: Deep Learning Enabled Topological Interaction Model for Energy
Prediction of Metal Clusters and its Application in Identifying Unique
Low Energy Isomers ,
R Aggarwal, A Gupta, V Chelur, CV Jawahar, UD Priyakumar -
DeepPocket: Ligand Binding Site Detection and Segmentation using 3D
Convolutional Neural Networks ,
V Bagal, R Aggarwal, PK Vinod, UD Priyakumar -
LigGPT: Molecular Generation using a Transformer-Decoder Model ,
Y Khare, V Bagal, M Mathew, A Devi, UD Priyakumar, CV Jawahar -
MMBERT: Multimodal BERT Pretraining for Improved Medical VQA ,
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 1033-1036
S Mehta, S Laghuvarapu, Y Pathak, A Sethi, M Alvala, UD Priyakumar -
Enhanced Sampling of Chemical Space for High Throughput Screening
Applications using Machine Learning ,
Y Pathak, S Mehta, UD Priyakumar -
Learning Atomic Interactions through Solvation Free Energy Prediction
Using Graph Neural Networks ,
Journal of Chemical Information and Modeling 61 (2), 689-698
A Karthikeyan, A Garg, PK Vinod, UD Priyakumar -
Machine learning based clinical decision support system for early
COVID-19 mortality prediction ,
Frontiers in public health 9
2020
Noor P S, Vinod PK -
Integrative analysis of DNA methylation and gene expression in Papillary Renal Cell Carcinoma ,
Molecular Genetics and Genomics
ohn Eric Steephen, Siva C. Obbineni, Sneha Kummetha, Raju S. Bapi -
HED-ID: An Affective Adaptation Model Explaining the Intensity-Duration Relationship of Emotion ,
IEEE Trans. Affect. Comput.
JR Annam, S Kalyanapu, S Ch, J Somala, SB Raju -
Classification of ECG Heartbeat Arrhythmia: A Review ,
Procedia Computer Science
R Sengupta, CM Lewis, RS Bapi -
Recalling a single object: going beyond the capacity debate ,
P Kaushik, J Naudé, SB Raju, F Alexandre -
A VTA GABAergic computational model of dissociated reward prediction error computation in classical conditioning ,
P Pattnaik, S Raghunathan, T Kalluri, P Bhimalapuram, CV Jawahar, -
Machine learning for accurate force calculations in molecular dynamics
simulations ,
The Journal of Physical Chemistry A 124 (34), 6954-6967
Y Pathak, S Laghuvarapu, S Mehta, UD Priyakumar -
Chemically interpretable graph interaction network for prediction of
pharmacokinetic properties of drug-like molecules ,
Proceedings of the AAAI Conference on Artificial Intelligence 34 (01), 873-880
S Laghuvarapu, Y Pathak, UD Priyakumar -
Band nn: A deep learning framework for energy prediction and geometry
optimization of organic small molecules ,
Journal of computational chemistry 41 (8), 790-799
S Alle, S Siddiqui, A Kanakan, A Garg, A Karthikeyan, N Mishra, -
COVID-19 Risk Stratification and Mortality Prediction in Hospitalized
Indian Patients ,
medRxiv
Y Pathak, KS Juneja, G Varma, M Ehara, UD Priyakumar -
Deep learning enabled inorganic material generator,
Physical Chemistry Chemical Physics 22 (46), 26935-26943
A Karthikeyan, A Garg, PK Vinod, UD Priyakumar - Machine learning based clinical decision support system for early covid-19 mortality prediction
Y Pathak, KS Juneja, G Varma, M Ehara, UD Priyakumar - Deep learning enabled inorganic material generator
P Pattnaik, S Raghunathan, T Kalluri, P Bhimalapuram, CV Jawahar, UD Priyakumar - Machine learning for accurate force calculations in molecular dynamics simulations, J. Phys. Chem. A 2020, 124, 6954-6967 (Virtual Special Issue on Machine Learning for Physical Chemistry) .
S Laghuvarapu, Y Pathak, UD Priyakumar - BAND NN: A deep learning framework for energy prediction and geometry optimization of organic small molecules , J. Comp. Chem. 2020, 41, 790-799 .
Y Pathak, S Laghuvarapu, S Mehta, U Priyakumar - Chemically interpretable graph interaction network for prediction of pharmacokinetic properties of drug-like molecules , 34th AAAI Conference, New York, 2020 .
Pathak, Y.; Mehta, S.; Priyakumar, U. D. - Learning Atomic Interactions through Solvation Free Energy Prediction Using Graph Neural Network , J. Chem. Informatics Model. 2020, under revision.
Chelur, V. R.; Priyakumar, U. D. Predicting the binding-site of a protein for druggable ligands from sequence-based features using Deep Learning , to be submitted.
Alle, S.; Garg, A.; Karthikeyan, A…. Sethuraman, R.; Subramanian, C.; Srivastava, M.; Chakravarthi, A.; Jacob, J.; Namagiri, M.; Konala, V.;… Vinod, P. K.; Priyakumar, U. D. Is Steroid Usage Responsible for Lower COVID19 Mortality Rate in India? to be submitted.
Mehta, S.; Laghuvarapu, S.; Pathak, Y.; Aftab, A.; Alvala, M.; Vinod, P. K.; Priyakumar, U. D. Enhanced Sampling of Chemical Space in Virtual Screening Applications using Machine Learning
Khare, Y.; Bagal, V.; Mathew, M.; Devi, A.; Priyakumar, U. D.; Jawahar, C. V. MMBERT: Multimodal BERT Pretraining for improved Medical VQA , Submitted.
Chauhan R, Vinod PK, Jawahar CV - Exploring the genetic-histological relationship in cancer, 2020 (under review)
Singh P, Menon A, Jawahar CV, Vinod PK - Histopathological image analysis of renal cancer using deep multi-instance learning , 2020 (under review)
Chauhan R, Jawahar CV, Vinod PK - AI applications to genomics and imaging - renal cancers , 2020 (under preparation)
Noor P S, Vinod PK - Integrative analysis of DNA methylation and gene expression in Papillary Renal Cell Carcinoma, Molecular Genetics and Genomics , 295, 807–824, 2020.
Moolamalaa STR and Vinod PK - Genome-scale metabolic network reconstruction and analysis of neuropsychiatric disorders , Comput. Biol. Med, 125, 103994, 2020
2019
NA Murugan, V Poongavanam, UD Priyakumar - Recent Advancements in Computing Reliable Binding Free Energies in
Drug Discovery Projects, Structural Bioinformatics: Applications in Preclinical Drug Discovery.
Murugan N.A., Poongavanam V., Priyakumar U.D. (2019) - Recent Advancements in Computing Reliable Binding Free Energies in Drug Discovery Projects, In: Mohan C. (eds) Structural Bioinformatics: Applications in Preclinical Drug Discovery Process. Challenges and Advances in Computational Chemistry and Physics, vol 27. Springer, Cham.
Tabibu, S.; Vinod, P. K.; Jawahar, C. V. - Pan-Renal Cell Carcinoma classification and survival prediction from histopathology images using deep learning, Sci. Rep. 2019, 9, 10509
Kumar, S.; Vinod, P. K - Single-cell transcriptomic analysis of pancreatic islets in health and type 2 diabetes, Int. J. Adv. Eng. Sci. Appl. Math (springer) 2019, 11, 105-118.
2018
Singh, N. P.; Bapi, R. S.; Vinod, P. K. - Machine learning models to predict the progression from early to late stages of papillary renal cell carcinoma, Comput. Biol. Med. 2018, 100, 92.
Chattopadhyay, A.; Zheng, M.; Waller, M.; Priyakumar, U. D. - A probabilistic framework for constructing temporal relations in replica exchange molecular trajectories, J. Chem. Theory Comput. 2018, 14, 3365.
A Chattopadhyay, M Zheng, MP Waller, UD Priyakumar -
A probabilistic framework for constructing temporal relations in replica
exchange molecular trajectories,
Journal of chemical theory and computation 14 (7), 3365-3380