Aditya Sonpal - Related publications

Affiliations: 
2016- Department of Chemical and Biological Engineering State University of New York, Buffalo, Buffalo, NY, United States 
Area:
MD Simulations, Database technology for chemistry
Website:
http://hachmannlab.cbe.buffalo.edu/index.php/team/graduate-students/aditya-sonpal/
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13 most relevant papers in past 60 days:
Year Citation  Score
2022 Chung Y, Vermeire FH, Wu H, Walker PJ, Abraham MH, Green WH. Group Contribution and Machine Learning Approaches to Predict Abraham Solute Parameters, Solvation Free Energy, and Solvation Enthalpy. Journal of Chemical Information and Modeling. PMID 35044781 DOI: 10.1021/acs.jcim.1c01103   
2022 Hanselman CL, Yin X, Miller DC, Gounaris CE. MatOpt: A Python Package for Nanomaterials Design Using Discrete Optimization. Journal of Chemical Information and Modeling. PMID 35023741 DOI: 10.1021/acs.jcim.1c00984   
2022 Hsu C, Nisonoff H, Fannjiang C, Listgarten J. Learning protein fitness models from evolutionary and assay-labeled data. Nature Biotechnology. PMID 35039677 DOI: 10.1038/s41587-021-01146-5   
2022 Saini V, Sharma A, Nivatia D. A machine learning approach for predicting the nucleophilicity of organic molecules. Physical Chemistry Chemical Physics : Pccp. PMID 34986215 DOI: 10.1039/d1cp05072a   
2022 Contessoto VG, de Oliveira VM, Leite VBP. Coarse-Grained Simulations of Protein Folding: Bridging Theory and Experiments. Methods in Molecular Biology (Clifton, N.J.). 2376: 303-315. PMID 34845616 DOI: 10.1007/978-1-0716-1716-8_16   
2022 Manna S, Loeffler TD, Batra R, Banik S, Chan H, Varughese B, Sasikumar K, Sternberg M, Peterka T, Cherukara MJ, Gray SK, Sumpter BG, Sankaranarayanan SKRS. Learning in continuous action space for developing high dimensional potential energy models. Nature Communications. 13: 368. PMID 35042872 DOI: 10.1038/s41467-021-27849-6   
2022 Gonçalves FB, Dutra LM, Silva RWC. Exact and computationally efficient Bayesian inference for generalized Markov modulated Poisson processes. Statistics and Computing. 32: 14. PMID 35013655 DOI: 10.1007/s11222-021-10074-y   
2022 Karthikeyan A, Priyakumar UD. Artificial intelligence: machine learning for chemical sciences. Journal of Chemical Sciences (Bangalore, India). 134: 2. PMID 34955617 DOI: 10.1007/s12039-021-01995-2   
2022 Hruska E, Gale A, Liu F. Bridging the Experiment-Calculation Divide: Machine Learning Corrections to Redox Potential Calculations in Implicit and Explicit Solvent Models. Journal of Chemical Theory and Computation. PMID 34991320 DOI: 10.1021/acs.jctc.1c01040   
2022 Ye G, Yin H, Chen T, Xu M, Nguyen QVH, Song J. Personalized On-Device E-health Analytics with Decentralized Block Coordinate Descent. Ieee Journal of Biomedical and Health Informatics. PMID 34986109 DOI: 10.1109/JBHI.2022.3140455   
2022 Mo L, Yu H, Hua W. Pruning Growing Self-Organizing Map Network for Human Physical Activity Identification. Journal of Healthcare Engineering. 2022: 9972406. PMID 35028128 DOI: 10.1155/2022/9972406   
2022 Brookes DH, Aghazadeh A, Listgarten J. On the sparsity of fitness functions and implications for learning. Proceedings of the National Academy of Sciences of the United States of America. 119. PMID 34937698 DOI: 10.1073/pnas.2109649118   
2022 Kwon Y, Lee D, Choi YS, Kang S. Uncertainty-aware prediction of chemical reaction yields with graph neural networks. Journal of Cheminformatics. 14: 2. PMID 35012654 DOI: 10.1186/s13321-021-00579-z