2023
Streamlining Pipeline Efficiency: a novel model-agnostic technique for accelerating conditional generative and virtual screening pipelines
Karthik Viswanathan , Manan Goel , Siddhartha Laghuvarapu , Girish Varma & U. Deva Priyakumar Scientific Reports
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MolOpt: Autonomous Molecular Geometry Optimization Using Multi-Agent Reinforcement Learning
Rohit Modee, Sarvesh Mehta, Siddhartha Laghuvarapu & U. Deva Priyakumar , The Journal OF Physical Chemistry B
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AI-assisted screening of oral potentially malignant disorders using smartphone-based photographic images
Prof. Vinod P.K , C V Jawahar, Ramanathan Sethuraman, Konal Varma Cancers, MDPI
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MeGen - generation of gallium metal clusters using reinforcement learning
Rohit Modee, Ashwini Verma, Kavita Joshi, U Deva Priyakumar Machine Learning: Science and Technology
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Latent Biases in Machine Learning Models for Predicting Binding Affinities Using Popular Data Sets
Ganesh Chandan Kanakala, Rishal Aggarwal, Divya Nayar, and U. Deva Priyakumar ACS OMEGA
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2022
Deep Reinforcement Learning for Molecular Inverse Problem of Nuclear Magnetic Resonance Spectra to Molecular Structure
B Sridharan, S Mehta, Y Pathak, UD Priyakumar, The Journal of Physical Chemistry Letters
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Modern Machine Learning for tackling inverse problems in Chemistry: Molecular Design to realization
Bhuvanesh Sridharan, Manan Goel, U. Deva Priyakumar ChemComm
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Efficient and enhanced sampling of drug-like chemical space for virtual screening and molecular design using modern machine learning methods
Manan Goel, Rishal Aggarwal, Bhuvanesh Sridharan, Pradeep Kumar Pal, U. Deva Priyakumar, WIRES
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MO-MEMES: A method for accelerating virtual screening using multi-objective Bayesian optimization
Sarvesh Mehta, Manan Goel, U Deva Priyakumar , Frontiers in Medicine
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PLAS-5k: Dataset of Protein-Ligand Affinities from Molecular Dynamics for Machine Learning Applications
Divya B. Korlepara, C. S. Vasavi, Shruti Jeurkar, Pradeep Kumar Pal, Subhajit Roy, Sarvesh Mehta, Shubham Sharma, Vishal Kumar, Charuvaka Muvva, Bhuvanesh Sridharan, Akshit Garg, Rohit Modee, Agastya P. Bhati, Divya Nayar & U. Deva Priyakumar , Scientific Data
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Structure - based drug repurposing: Traditional and advanced A/ML-aided methods
C Choudhury, NA Murugan, UD Priyakumar , Drug Discovery Today
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Deep Reinforcement Learning for Molecular Inverse Problem of Nuclear Magnetic Resonance Spectra to Molecular Structure
Bhuvanesh Sridharan, Sarvesh Mehta, Yashaswi Pathak, U. Deva Priyakumar The Journal of Physical Chemistry
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Birds - binding residue detection from protein sequences using deep resnets
VR Chelur, UD Priyakumar , Journal of Chemical Information and Modelling
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The Times They Are-a-Changin”: The Effect of the Covid-19 Pandemic on Online Music Sharing in India
Desur, P., Kamble, T., Krause, A., Kumaraguru, P., Alluri, V. ,Journal of ,2022.
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Modern AI/ML Methods for Healthcare: Opportunities and Challenges
Akshit Garg, Vijay Vignesh Venkataramani, Akshaya Karthikeyan, U. Deva Priyakumar , Journal of ,2022.
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Bytes, Pixels, & Bases: Machine Learning in Imaging-omics for Renal Cell Carcinoma
Chauhan R, Jawahar CV and Vinod P K , Artificial Intelligence in Cancer Diagnosis and Prognosis, IOP publishing ,2022
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Mathematical modelling of neurodegeneration
Nishtha P, Vinod P K , Journal of Frontiers in Oncology ,2022
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Deep Learning approach for classification and interpretation of Autism Spectrum Disorder
Krishna Chandra Prasad Pindi, Yash Khare, Vinod P.K., Bapi Raju S, Kamalaker Dadi , Journal ofFrontiers in Oncology ,2022
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Exploring histological similarities across cancers from a deep learning perspective
Ashish Menon, Piyush Singh, P. K. Vinod, C V Jawahar, Journal ofFrontiers in Oncology ,2022.
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Systems-level analysis of transcriptome reorganization during liver regeneration
Manisri Porukala, P.K. Vinod , Journal of Molecular Omics ,2022
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2021
Clinico-genomic analysis reveals mutations associated with COVID-19 disease severity: possible modulation by RNA structure
P Mehta, S Alle, A Chaturvedi, A Swaminathan, S Saifi, R Maurya , Partha Chattopadhyay , Priti Devi, R Chauhan, Akshay Kanakan, J S Vasudevan, R Sethuraman, S Chidambaram, M Srivastava, A Chakravarthi, Johnny Jacob, Madhuri Namagiri, Varma Konala, Sujeet Jha, U. Deva Priyakumar, P. K. Vinod and Rajesh Pandey Pathogens
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Mining subgraph coverage patterns from graph transactions
AS Reddy, PK Reddy, A Mondal, UDPriyakumar , International Journal of Data Science and Analytics
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Motor Learning Behaviors involved in Internally-Guided Motor Skill Learning
K Bera, A Shukla, RS Bapi , Journal of Frontiers in Psychology,2021
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Artificial Intelligence:Machine Learning for Chemical Sciences
Akshaya Karthikeyan, U. Deva Priyakumar, Journal of Chemical Sciences,2021
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Molecular Representations for Machine Learning Applications in Chemistry
Shampa Raghunathan, U. Deva Priyakumar, International Journal of Quantum Chemistry ,2021
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Learning Atomic Interactions through Solvation Free Energy Prediction Using Graph Neural Networks
Yashaswi Pathak, Sarvesh Mehta, U Deva Priyakumar, Journal of Chemical Information and Modeling,61,2,2021
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Machine learning based clinical decision support system for early covid-19 mortality prediction
A Karthikeyan, A Garg, PK Vinod, UD Priyakumar, Frontiers in Public health,2021
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Numerical Magnitude Affects Accuracy but Not Precision of Temporal Judgments
A Shukla, RS Bapi, Frontiers in Human Neuroscience, 14, 2021
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Motor Chunking in Internally Guided Sequencing
K Bera, A Shukla, RS Bapi, Brain Sciences, 11, 3, 2021
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Learning Behaviors involved in Internally-Guided Motor Skill Learning
K Bera, A Shukla, RS Bapi, Frontiers in Psychology, 12, 2021
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DeepPocket: Ligand Binding Site Detection and Segmentation using 3D Convolutional Neural Networks
R Aggarwal, A Gupta, V Chelur, CV Jawahar, UD Priyakumar, American Chemical Society, 2021
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MolGPT: Molecular Generation using a Transformer-Decoder Model
V Bagal, R Aggarwal, PK Vinod, UD Priyakumar, 2021
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MEMES: Machine learning framework for Enhanced MolEcular Screening
S Mehta, S Laghuvarapu, Y Pathak, A Sethi, M Alvala, UD Priyakumar, Journal of Chemical Sciences, 12, 35, 2021
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APObind: A Dataset of Ligand Unbound Protein Conformations for Machine Learning Applications in De Novo Drug Design
R Aggarwal, A Gupta, UD Priyakumar, arXiv, 2021
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Brain Affective System Inspired Control Architecture: An Application to Nonlinear System
Md. Qutubuddin, Tilahun Kochito Gibo, Raju S. Bapi, Narri Yadaiah, IEEE Access, 9, 2021
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Effects of Meditation on Structural Changes of the Brain in Patients With Mild Cognitive Impairment or Alzheimer’s Disease Dementia
Dwivedi M, Dubey N, Pansari AJ, Bapi RS, Das M, Guha M, Banerjee R, Pramanick G, Basu J and Ghosh A, Frontiers in Human Neuroscience, 2021
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SCONES: Self-Consistent Neural Network for Protein Stability Prediction Upon Mutatio
YS BL, S Raghunathan, UD Priyakumar, The Journal of Physical Chemistry, 2021
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MoleGuLAR: Molecule Generation using Reinforcement Learning with Alternating Rewards
M Goel, S Raghunathan, S Laghuvarapu, UD Priyakumar, Journal of Chemical Information and Modeling, 2021
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Clinico-Genomic AnalysisModulation by RNA Reveals Mutations Associated with Covid-19 Diisease Severity: Possible Modulation by RNA Structure
P Mehta, S Alle, A Chaturvedi, A Swaminathan, S Saifi, R Maurya, Pathogens, 10, 9, 2021
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Host metabolic reprogramming in response to SARS-CoV-2 infection: A system biology approach
STR Moolamalla, R Balasubramanian, R Chauhan, UD Priyakumar, PK Vinod, Microbial Pathogenesis, 158, 2021
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Benchmark study on deep neural network potentials for small organic molecules
Rohit Modee, Siddhartha Laghuvarapu, U. Deva Priyakumar, Journal of Computational Chemistry, 2021
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2020
BAND NN: A deep learning framework for energy prediction and geometry optimization of organic small molecules
S Laghuvarapu, Y Pathak, UD Priyakumar, Journal of Computational Chemistry,41,8,2020.
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Integrative analysis of DNA methylation and gene expression in Papillary Renal Cell Carcinoma
Noor P S, Vinod PK, Molecular Genetics and Genomics, 295, 2020
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HED-ID: An Affective Adaptation Model Explaining the Intensity-Duration Relationship of Emotion
ohn Eric Steephen, Siva C. Obbineni, Sneha Kummetha, Raju S. Bapi, IEEE Trans. Affect. Comput., 11, 4, 2020.
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Recalling a single object: going beyond the capacity debate
R Sengupta, CM Lewis, RS Bapi, BioRxiv, 2020
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A VTA GABAergic computational model of dissociated reward prediction error computation in classical conditioning
P Kaushik, J Naudé, SB Raju, F Alexandre, Science Gate,2020
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2019
BAND NN: A deep learning framework for energy prediction and geometry optimization of organic small molecules
S Laghuvarapu, Y Pathak, UD Priyakumar , Journal of Computational Chemistry
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