Journal published by Researchers in Health Care.

| 2024 | | 2023 | 2022 | 2021 | 2020 |

2024

  • Manisri Porukala, P K Vinod , Gene expression signatures of stepwise progression of Hepatocellular Carcinoma , PLOS ONE
  • Divya B Korlepara, Vasavi CS, Rakesh Srivastava, Pradeep Kumar Pal, Saalim H Raza, Vishal Kumar, Shivam Pandit, Aathira G Nair, Sanjana Pandey, Shubham Sharma, Shruti Jeurkar, Kavita Thakran, Reena Jaglan, Shivangi Verma, Indhu Ramachandran, Prathit Chatterjee, Divya Nayar, U Deva Priyakumar , PLAS-20k: Extended Dataset of Protein-Ligand Affinities from MD Simulations for Machine Learning Applications , Scientific Data
  • Sriram Devata, Bhuvanesh Sridharan, Sarvesh Mehta, Yashawi Pathak, Siddhartha Laghuvarapu, Girish Varma, U. Deva Priyakumar , DeepSPInN - deep reinforcement learning for molecular struture prediction from infrared and NMR spectra , Digital Discovery
  • Rakesh Sengupta, Christelle M. Lewis, Raju S. Bapi , Recalling a single object: going beyond the capacity debate , bioRxiv
  • Kapali Suri, Madhu Ramesh, Mansi Bhandari, Vishakha Gupta, Virendra Kumar, Thimmaiah Govindaraju, N. Arul Murugan, Role of Amyloidogenic and Non-Amyloidogenic Protein Spaces in Neurodegenerative Diseases and Their Mitigation Using Theranostic Agents , ChemBioChem

2023

  • Karthik Viswanathan , Manan Goel , Siddhartha Laghuvarapu , Girish Varma & U. Deva Priyakumar , Streamlining Pipeline Efficiency: a novel model-agnostic technique for accelerating conditional generative and virtual screening pipelines , Scientific Reports
  • Rohit Modee, Sarvesh Mehta, Siddhartha Laghuvarapu & U. Deva Priyakumar , MolOpt: Autonomous Molecular Geometry Optimization Using Multi-Agent Reinforcement Learning​ , The Journal OF Physical Chemistry B
  • Prof. Vinod P.K , C V Jawahar, Ramanathan Sethuraman, Konal Varma , AI-assisted screening of oral potentially malignant disorders using smartphone-based photographic images , Cancers, MDPI
  • Rohit Modee, Ashwini Verma, Kavita Joshi, U Deva Priyakumar, MeGen - generation of gallium metal clusters using reinforcement learning , Machine Learning: Science and Technology
  • Ganesh Chandan Kanakala, Rishal Aggarwal, Divya Nayar, and U. Deva Priyakumar , Latent Biases in Machine Learning Models for Predicting Binding Affinities Using Popular Data Sets , ACS OMEGA

2022

  • B Sridharan, S Mehta, Y Pathak, UD Priyakumar, Deep Reinforcement Learning for Molecular Inverse Problem of Nuclear Magnetic Resonance Spectra to Molecular Structure , The Journal of Physical Chemistry Letters
  • Bhuvanesh Sridharan, Manan Goel, U. Deva Priyakumar, Modern Machine Learning for tackling inverse problems in Chemistry: Molecular Design to realization , ChemComm
  • Manan Goel, Rishal Aggarwal, Bhuvanesh Sridharan, Pradeep Kumar Pal, U. Deva Priyakumar, Efficient and enhanced sampling of drug-like chemical space for virtual screening and molecular design using modern machine learning methods , WIRES
  • Sarvesh Mehta, Manan Goel, U Deva Priyakumar, MO-MEMES: A method for accelerating virtual screening using multi-objective Bayesian optimization , Frontiers in Medicine
  • 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 , PLAS-5k: Dataset of Protein-Ligand Affinities from Molecular Dynamics for Machine Learning Applications , Scientific Data
  • C Choudhury, NA Murugan, UD Priyakumar , Structure - based drug repurposing: Traditional and advanced A/ML-aided methods , Drug Discovery Today
  • Bhuvanesh Sridharan, Sarvesh Mehta, Yashaswi Pathak, U. Deva Priyakumar , Deep Reinforcement Learning for Molecular Inverse Problem of Nuclear Magnetic Resonance Spectra to Molecular Structure , The Journal of Physical Chemistry
  • VR Chelur, UD Priyakumar , Birds - binding residue detection from protein sequences using deep resnets , Journal of Chemical Information and Modelling
  • Desur, P., Kamble, T., Krause, A., Kumaraguru, P., Alluri, V. , The Times They Are-a-Changin”: The Effect of the Covid-19 Pandemic on Online Music Sharing in India , Journal of ,2022.
  • Akshit Garg, Vijay Vignesh Venkataramani, Akshaya Karthikeyan, U. Deva Priyakumar , Modern AI/ML Methods for Healthcare: Opportunities and Challenges , Journal of ,2022.
  • Chauhan R, Jawahar CV and Vinod P K , Bytes, Pixels, & Bases: Machine Learning in Imaging-omics for Renal Cell Carcinoma , Artificial Intelligence in Cancer Diagnosis and Prognosis, IOP publishing ,2022
  • Nishtha P, Vinod P K , Mathematical modelling of neurodegeneration , Journal of Frontiers in Oncology ,2022
  • Krishna Chandra Prasad Pindi, Yash Khare, Vinod P.K., Bapi Raju S, Kamalaker Dadi , Deep Learning approach for classification and interpretation of Autism Spectrum Disorder , Journal ofFrontiers in Oncology , 2022
  • Ashish Menon, Piyush Singh, P. K. Vinod, C V Jawahar, Exploring histological similarities across cancers from a deep learning perspective , Journal ofFrontiers in Oncology ,2022.
  • Manisri Porukala, P.K. Vinod , Systems-level analysis of transcriptome reorganization during liver regeneration , Journal of Molecular Omics ,2022

2021

  • 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 Clinico-genomic analysis reveals mutations associated with COVID-19 disease severity: possible modulation by RNA structure , Pathogens
  • AS Reddy, PK Reddy, A Mondal, UD Priyakumar, Mining subgraph coverage patterns from graph transactions , International Journal of Data Science and Analytics
  • K Bera, A Shukla, RS Bapi , Motor Learning Behaviors involved in Internally-Guided Motor Skill Learning , Journal of Frontiers in Psychology, 2021
  • Akshaya Karthikeyan, U. Deva Priyakumar, Artificial Intelligence:Machine Learning for Chemical Sciences , Journal of Chemical Sciences, 2021
  • Shampa Raghunathan, U. Deva Priyakumar, Molecular Representations for Machine Learning Applications in Chemistry , International Journal of Quantum Chemistry , 2021
  • Yashaswi Pathak, Sarvesh Mehta, U Deva Priyakumar, Learning Atomic Interactions through Solvation Free Energy Prediction Using Graph Neural Networks , Journal of Chemical Information and Modeling,61,2,2021
  • 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,2021
  • A Shukla, RS Bapi, Numerical Magnitude Affects Accuracy but Not Precision of Temporal Judgments , Frontiers in Human Neuroscience, 14, 2021
  • K Bera, A Shukla, RS Bapi, Motor Chunking in Internally Guided Sequencing , Brain Sciences, 11, 3, 2021
  • K Bera, A Shukla, RS Bapi , Learning Behaviors involved in Internally-Guided Motor Skill Learning , Frontiers in Psychology, 12, 2021
  • R Aggarwal, A Gupta, V Chelur, CV Jawahar, UD Priyakumar, DeepPocket: Ligand Binding Site Detection and Segmentation using 3D Convolutional Neural Networks , American Chemical Society, 2021
  • V Bagal, R Aggarwal, PK Vinod, UD Priyakumar , MolGPT: Molecular Generation using a Transformer-Decoder Model , 2021
  • S Mehta, S Laghuvarapu, Y Pathak, A Sethi, M Alvala, UD Priyakumar, MEMES: Machine learning framework for Enhanced MolEcular Screening , Journal of Chemical Sciences, 12, 35, 2021
  • 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
  • Md. Qutubuddin, Tilahun Kochito Gibo, Raju S. Bapi, Narri Yadaiah, Brain Affective System Inspired Control Architecture: An Application to Nonlinear System , IEEE Access, 9, 2021
  • Dwivedi M, Dubey N, Pansari AJ, Bapi RS, Das M, Guha M, Banerjee R, Pramanick G, Basu J and Ghosh A, , Effects of Meditation on Structural Changes of the Brain in Patients With Mild Cognitive Impairment or Alzheimer’s Disease Dementia , Frontiers in Human Neuroscience, 2021
  • YS BL, S Raghunathan, UD Priyakumar, SCONES: Self-Consistent Neural Network for Protein Stability Prediction Upon Mutatio , The Journal of Physical Chemistry, 2021
  • M Goel, S Raghunathan, S Laghuvarapu, UD Priyakumar , MoleGuLAR: Molecule Generation using Reinforcement Learning with Alternating Rewards , Journal of Chemical Information and Modeling, 2021
  • P Mehta, S Alle, A Chaturvedi, A Swaminathan, S Saifi, R Maurya, Clinico-Genomic AnalysisModulation by RNA Reveals Mutations Associated with Covid-19 Diisease Severity: Possible Modulation by RNA Structure , Pathogens, 10, 9, 2021
  • STR Moolamalla, R Balasubramanian, R Chauhan, UD Priyakumar, PK Vinod, , Host metabolic reprogramming in response to SARS-CoV-2 infection: A system biology approach , Microbial Pathogenesis, 158, 2021
  • Rohit Modee, Siddhartha Laghuvarapu, U. Deva Priyakumar, Benchmark study on deep neural network potentials for small organic molecules , Journal of Computational Chemistry, 2021

2020

  • 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,41,8,2020.
  • Noor P S, Vinod PK, , Integrative analysis of DNA methylation and gene expression in Papillary Renal Cell Carcinoma , Molecular Genetics and Genomics, 295, 2020
  • 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., 11, 4, 2020.
  • R Sengupta, CM Lewis, RS Bapi, Recalling a single object: going beyond the capacity debate , BioRxiv, 2020
  • P Kaushik, J Naudé, SB Raju, F Alexandre, A VTA GABAergic computational model of dissociated reward prediction error computation in classical conditioning , Science Gate, 2020

2019

  • 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