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Recent progress in Large Language Models (LLMs) has drawn attention to their potential for accelerating drug discovery.
Comprehensive analysis of kinase inhibitor selectivity
Mindy I Davis, Jeremy P Hunt, Sanna Herrgard, Pietro Ciceri, Lisa M Wodicka, Gabriel Pallares, Michael Hocker, Daniel K Treiber, and Patrick P Zarrinkar. 2011 · 2011
Earlier work this paper cites.
Moleculenet: a benchmark for molecular machine learning
Zhenqin Wu, Bharath Ramsundar, Evan N Feinberg, Joseph Gomes, Caleb Geniesse, Ajay S Pappu, Karl Leswing, and Vijay Pande. 2018 · 2018
Earlier work this paper cites.
Deepdta: Deep drug–target binding affinity prediction
Hakime Öztürk, Arzucan Özgür, and Elif Ozkirimli. 2018 · 2018
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Drug repurposing: progress, challenges and recommendations
Sudeep Pushpakom, Francesco Iorio, Patrick A Eyers, K Jane Escott, Shirley Hopper, Andrew Wells, Andrew Doig, Tim Guilliams, Joanna Latimer, Christine McNamee, et al. 2019 · 2019
Earlier work this paper cites.
Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences
Alexander Rives, Joshua Meier, Tom Sercu, Siddharth Goyal, Zeming Lin, Jason Liu, Demi Guo, Myle Ott, C. Lawrence Zitnick, Jerry Ma, and Rob Fergus. 2019 · 2019
Earlier work this paper cites.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush. 2020 · 2020
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Data-driven detection of subtype-specific differentially expressed genes
Lulu Chen, Yingzhou Lu, Chiung-Ting Wu, Robert Clarke, Guoqiang Yu, Jennifer E Van Eyk, David M Herrington, and Yue Wang. 2021 · 2021
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Therapeutics data commons: Machine learning datasets and tasks for drug discovery and development
Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, and Marinka Zitnik. 2021 · 2021
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Dgl-lifesci: An open-source toolkit for deep learning on graphs in life science
Mufei Li, Jinjing Zhou, Jiajing Hu, Wenxuan Fan, Yangkang Zhang, Yaxin Gu, and George Karypis. 2021 · 2021
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A deep learning framework for high-throughput mechanism-driven phenotype compound screening and its application to covid-19 drug repurposing
Thai-Hoang Pham, Yue Qiu, Jucheng Zeng, Lei Xie, and Ping Zhang. 2021 · 2021
Earlier work this paper cites.
Validating adme qsar models using marketed drugs
V. B. Siramshetty, P. Shah, et al. 2021 · 2021
Earlier work this paper cites.
DDN2.0: R and python packages for differential dependency network analysis of biological systems
Bai Zhang, Yi Fu, Yingzhou Lu, Zhen Zhang, Robert Clarke, Jennifer E Van Eyk, David M Herrington, and Yue Wang. 2021 · 2021
Earlier work this paper cites.
Artificial intelligence foundation for therapeutic science
Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W Coley, Cao Xiao, Jimeng Sun, and Marinka Zitnik. 2022 · 2022
Earlier work this paper cites.
Language models of protein sequences at the scale of evolution enable accurate structure prediction
Zeming Lin, Halil Akin, Roshan Rao, Brian Hie, Zhongkai Zhu, Wenting Lu, Allan dos Santos Costa, Maryam Fazel-Zarandi, Tom Sercu, Sal Candido, et al. 2022 · 2022
Cited alongside, same era.
COT: an efficient and accurate method for detecting marker genes among many subtypes
Yingzhou Lu, Chiung-Ting Wu, Sarah J Parker, Zuolin Cheng, Georgia Saylor, Jennifer E Van Eyk, Guoqiang Yu, Robert Clarke, David M Herrington, and Yue Wang. 2022 · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, and Denny Zhou. 2022 · 2022
Cited alongside, same era.
Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, and Ting Liu. 2023 · 2023
Cited alongside, same era.
A survey on large language models for code generation
Juyong Jiang, Fan Wang, Jiasi Shen, Sungju Kim, and Sunghun Kim. 2024 · 2024
Closest in time.
Mmedagent: Learning to use medical tools with multi-modal agent
Binxu Li, Tiankai Yan, Yuanting Pan, Jie Luo, Ruiyang Ji, Jiayuan Ding, Zhe Xu, Shilong Liu, Haoyu Dong, Zihao Lin, and Yixin Wang. 2024a · 2024
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Flexmol: A flexible toolkit for benchmarking molecular relational learning
Sizhe Liu, Jun Xia, Lecheng Zhang, Yuchen Liu, Yue Liu, Wenjie Du, Zhangyang Gao, Bozhen Hu, Cheng Tan, Hongxin Xiang, and Stan Z. Li. 2024 · 2024
Closest in time.
Augmenting large language models with chemistry tools
Andres M. Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D. White, and Philippe Schwaller. 2024 · 2024
Closest in time.
Pharmabench: Enhancing admet benchmarks with large language models
Zhangming Niu, Xianglu Xiao, Wenfan Wu, Qiwei Cai, Yinghui Jiang, Wangzhen Jin, Minhao Wang, Guojian Yang, Lingkang Kong, Xurui Jin, Guang Yang, and Hongming Chen. 2024 · 2024
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MultiTool-CoT: GPT-3 can use multiple external tools with chain of thought prompting
Tatsuro Inaba, Hirokazu Kiyomaru, Fei Cheng, and Sadao Kurohashi. 2023 · 2023
Cited alongside, same era.
Rdkit: Open-source cheminformatics
Greg Landrum. 2023 · 2023
Cited alongside, same era.
Paperqa: Retrieval-augmented generative agent for scientific research
Jakub Lála, Odhran O’Donoghue, Aleksandar Shtedritski, Sam Cox, Samuel G. Rodriques, and Andrew D. White. 2023 · 2023
Cited alongside, same era.
Chemberta-2: Fine-tuning for molecule’s HIV replication inhibition prediction
Sylwia Nowakowska. 2023 · 2023
Cited alongside, same era.
Tool learning with foundation models
Yujia Qin, Shengding Hu, Yankai Lin, Weize Chen, Ning Ding, Ganqu Cui, Zheni Zeng, Yufei Huang, Chaojun Xiao, Chi Han, Yi Ren Fung, Yusheng Su, Huadong Wang, Cheng Qian, Runchu Tian, Kunlun Zhu, Shihao Liang, Xingyu Shen, Bokai Xu, Zhen Zhang, Yining Ye, Bowen Li, Ziwei Tang, Jing Yi, Yuzhang Zhu, Zhenning Dai, Lan Yan, Xin Cong, Yaxi Lu, Weilin Zhao, Yuxiang Huang, Junxi Yan, Xu Han, Xian Sun, Dahai Li, Jason Phang, Cheng Yang, Tongshuang Wu, Heng Ji, Zhiyuan Liu, and Maosong Sun. 2023 · 2023
Cited alongside, same era.
Toolformer: Language models can teach themselves to use tools
Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom. 2023 · 2023
Cited alongside, same era.
Jun Xia, Lecheng Zhang, Xiao Zhu, Yue Liu, Zhangyang Gao, Bozhen Hu, Cheng Tan, Jiangbin Zheng, Siyuan Li, and Stan Z. Li. 2023 · 2023
Cited alongside, same era.
ReAct: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2023 · 2023
Cited alongside, same era.
Closest in time.
Chatgpt: Gpt-4o-2024-08-06
OpenAI . 2024 · 2024
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Agentic retrieval-augmented generation for time series analysis
Chidaksh Ravuru, Sagar Srinivas Sakhinana, and Venkataramana Runkana. 2024 · 2024
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Aide: The machine learning engineer agent
WecoAI. 2024 · 2024
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Sion Yoon, Tae Eun Kim, and Yoo Jung Oh. 2024 · 2024
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Clinicalagent: Clinical trial multi-agent with large language model-based reasoning
Ling Yue, Sixue Xing, Jintai Chen, and Tianfan Fu. 2024 · 2024
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Pybiomed: A toolkit for calculating molecular descriptors and analyzing biological molecules
CBDD Group. 2020 · 2025
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Sp-dti: Subpocket-informed transformer for drug-target interaction prediction
Sizhe Liu, Yuchen Liu, Haofeng Xu, Jun Xia, and Stan Z. Li. 2025 · 2025
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