BSim: an agent-based tool for modeling bacterial populations in systems and synthetic biology by Gorochowski, Thomas E, Matyjaszkiewicz, Antoni, Todd, Thomas, Oak, Neeraj, Kowalska, Kira, Reid, Stephen, Tsaneva-Atanasova, Krasimira T, Savery, Nigel J, Grierson, Claire S, di Bernardo, Mario

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Apparent strength conceals instability in a model for the collapse of historical states by Lawson, Daniel John, Oak, Neeraj

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Performance comparison of renewable incentive schemes using optimal control by OAK, Neeraj, LAWSON, Daniel, CHAMPNEYS, Alan

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Apparent strength conceals instability in a model for the collapse of historical states by Lawson, Daniel John, Oak, Neeraj

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High-Throughput Virtual Screening and Validation of a SARS-CoV‑2 Main Protease Noncovalent Inhibitor by Clyde, Austin, Galanie, Stephanie, Kneller, Daniel W, Ma, Heng, Babuji, Yadu, Blaiszik, Ben, Brace, Alexander, Brettin, Thomas, Chard, Kyle, Chard, Ryan, Coates, Leighton, Foster, Ian, Hauner, Darin, Kertesz, Vilmos, Kumar, Neeraj, Lee, Hyungro, Li, Zhuozhao, Merzky, Andre, Schmidt, Jurgen G, Tan, Li, Titov, Mikhail, Trifan, Anda, Turilli, Matteo, Van Dam, Hubertus, Chennubhotla, Srinivas C, Jha, Shantenu, Kovalevsky, Andrey, Ramanathan, Arvind, Head, Martha S, Stevens, Rick

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Effect of GaN surface treatment on Al2O3/ n -GaN MOS capacitors by Hossain, Tashfin, Wei, Daming, Edgar, James H., Garces, Nelson Y., Nepal, Neeraj, Hite, Jennifer K., Mastro, Michael A., Eddy, Charles R., Meyer, Harry M.

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AI-Accelerated Design of Targeted Covalent Inhibitors for SARS-CoV‑2 by Joshi, Rajendra P., Schultz, Katherine J., Wilson, Jesse William, Kruel, Agustin, Varikoti, Rohith Anand, Kombala, Chathuri J., Kneller, Daniel W., Galanie, Stephanie, Phillips, Gwyndalyn, Zhang, Qiu, Coates, Leighton, Parvathareddy, Jyothi, Surendranathan, Surekha, Kong, Ying, Clyde, Austin, Ramanathan, Arvind, Jonsson, Colleen B., Brandvold, Kristoffer R., Zhou, Mowei, Head, Martha S., Kovalevsky, Andrey, Kumar, Neeraj

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Discovery of a Damped Lyα Absorber Originating in a Spectacular Interacting Dwarf Galaxy Pair at z = 0.026 by Boettcher, Erin, Gupta, Neeraj, Chen, Hsiao-Wen, Chen, Mandy C., Józsa, Gyula I. G., Rudie, Gwen C., Cantalupo, Sebastiano, Johnson, Sean D., Balashev, S. A., Combes, Françoise, Cooksey, Kathy L., Faucher-Giguère, Claude-André, Krogager, Jens-Kristian, Lopez, Sebastian, Momjian, Emmanuel, Noterdaeme, Pasquier, Petitjean, Patrick, Rafelski, Marc, Srianand, Raghunathan, Walth, Gregory L., Zahedy, Fakhri S.

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Co-design Center for Exascale Machine Learning Technologies (ExaLearn) by Alexander, Francis J, Ang, James, Bilbrey, Jenna A, Balewski, Jan, Casey, Tiernan, Chard, Ryan, Choi, Jong, Choudhury, Sutanay, Debusschere, Bert, DeGennaro, Anthony M, Dryden, Nikoli, Ellis, J Austin, Foster, Ian, Cardona, Cristina Garcia, Ghosh, Sayan, Harrington, Peter, Huang, Yunzhi, Jha, Shantenu, Johnston, Travis, Kagawa, Ai, Kannan, Ramakrishnan, Kumar, Neeraj, Liu, Zhengchun, Maruyama, Naoya, Matsuoka, Satoshi, McCarthy, Erin, Mohd-Yusof, Jamaludin, Nugent, Peter, Oyama, Yosuke, Proffen, Thomas, Pugmire, David, Rajamanickam, Sivasankaran, Ramakrishniah, Vinay, Schram, Malachi, Seal, Sudip K, Sivaraman, Ganesh, Sweeney, Christine, Tan, Li, Thakur, Rajeev, Van Essen, Brian, Ward, Logan, Welch, Paul, Wolf, Michael, Xantheas, Sotiris S, Yager, Kevin G, Yoo, Shinjae, Yoon, Byung-Jun

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Pyramiding of genes for grain protein content, grain quality, and rust resistance in eleven Indian bread wheat cultivars: a multi-institutional effort by Gupta, Pushpendra K., Balyan, Harindra S., Chhuneja, Parveen, Jaiswal, Jai P., Tamhankar, Shubhada, Mishra, Vinod K., Bains, Navtej S., Chand, Ramesh, Joshi, Arun K., Kaur, Satinder, Kaur, Harinderjeet, Mavi, Gurvinder S., Oak, Manoj, Sharma, Achla, Srivastava, Puja, Sohu, Virinder S., Prasad, Pramod, Agarwal, Priyanka, Akhtar, Moin, Badoni, Saurabh, Chaudhary, Reeku, Gahlaut, Vijay, Gangwar, Rishi Pal, Gautam, Tinku, Jaiswal, Vandana, Kumar, Ravi Shekhar, Kumar, Sachin, Shamshad, M., Singh, Anupama, Taygi, Sandhya, Vasistha, Neeraj Kumar, Vishwakarma, Manish Kumar

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Identifying intragenic functional modules of genomic variations associated with cancer phenotypes by learning representation of association networks by Kim, Minsu, Huffman, Jennifer E, Justice, Amy, Goethert, Ian, Agasthya, Greeshma, Danciu, Ioana

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