2021

  • 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