LLM(Large Language Model)4Mol is a comprehensive repository dedicated to the collection and exploration of studies utilizing large language models for molecular design, protein research, and material science. This repository serves as a central hub for researchers, scientists, and enthusiasts interested in leveraging the power of language models for advancing our understanding and applications in these domains. Discover state-of-the-art techniques, novel approaches, and cutting-edge research papers that harness the potential of AI-powered language models in unraveling the complexities of Biomedical Text, RNA/DNA, Molecules, Peptides, Proteins, Antibody, and Materials. Join our vibrant community and contribute to the exciting advancements in the field of LLM4Mol!

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Generative AI and Deep Learning for molecular/drug design
https://github.com/AspirinCode/papers-for-molecular-design-using-DL

List of papers about Proteins Design using Deep Learning
https://github.com/Peldom/papers_for_protein_design_using_DL

Large Language Models in Chemistry
https://github.com/alxfgh/Large-Language-Models-in-Chemistry

• LLM4Biomedical Text
• LLM4Small Molecule
• LLM4RNA/DNA
• LLM4Peptide
• LLM4Protein
• LLM4Antibody
• LLM4Clinical
• LLM4Chemistry
• LLM4Material

• Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health [2023]
  Tian, Shubo, Qiao Jin, Lana Yeganova, Po-Ting Lai, Qingqing Zhu, Xiuying Chen, Yifan Yang et al.
  arXiv:2306.10070 (2023)

• Large language models are universal biomedical simulators [2023]
  Schaefer, Moritz, Stephan Reichl, Rob ter Horst, Adele M. Nicolas, Thomas Krausgruber, Francesco Piras, Peter Stepper, Christoph Bock, and Matthias Samwald.
  bioRxiv (2023) | code

• Fine-tuning large neural language models for biomedical natural language processing [2023]
  Tinn, Robert, Hao Cheng, Yu Gu, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, and Hoifung Poon.
  Patterns 4.4 (2023) | code

• A Platform for the Biomedical Application of Large Language Models [2023]
  Lobentanzer, Sebastian, and Julio Saez-Rodriguez.
  arXiv:2305.06488v2 | code

• Large language models in biomedical natural language processing: benchmarks, baselines, and recommendations [2023]
  Chen, Qingyu, Jingcheng Du, Yan Hu, Vipina Kuttichi Keloth, Xueqing Peng, Kalpana Raja, Rui Zhang, Zhiyong Lu, and Hua Xu.
  arXiv:2305.16326v1 | code

• BiomedGPT: A Unified and Generalist Biomedical Generative Pre-trained Transformer for Vision, Language, and Multimodal Tasks [2023]
  Zhang, K., Yu, J., Yan, Z., Liu, Y., Adhikarla, E., Fu, S., ... & Sun, L.
  arXiv:2305.17100v1 | code

• BioMedLM: a Domain-Specific Large Language Model for Biomedical Text [2022]
  Paper | code

• Empowering Molecule Discovery for Molecule-Caption Translation with LargeLanguage Models: A ChatGPT Perspective [2023]
  Jiatong Li, Yunqing Liu, Wenqi Fan, Xiao-Yong Wei, Hui Liu, Jiliang Tang, Qing Li
  arXiv:2306.06615 (2023) | code

• Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language [2023]
  Yin Fang, Xiaozhuan Liang, Ningyu Zhang, Kangwei Liu, Rui Huang, Zhuo Chen, Xiaohui Fan, Huajun Chen
  arXiv:2303.03363 (2023) | code

• Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models [2023]
  Yin Fang, Xiaozhuan Liang, Ningyu Zhang, Kangwei Liu, Rui Huang, Zhuo Chen, Xiaohui Fan, Huajun Chen
  arXiv:2306.08018v1 | code

• MolReGPT: Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective [2023]
  Li, Jiatong, Yunqing Liu, Wenqi Fan, Xiao-Yong Wei, Hui Liu, Jiliang Tang, and Qing Li.
  arXiv:2306.06615v1 | code

• HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution [2023]
  Eric Nguyen, Michael Poli, Marjan Faizi, Armin Thomas, Callum Birch-Sykes, Michael Wornow, Aman Patel, Clayton Rabideau, Stefano Massaroli, Yoshua Bengio, Stefano Ermon, Stephen A. Baccus, Chris Ré.
  arXiv:2306.15794v1

• DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome [2021]
  Ji, Yanrong, Zhihan Zhou, Han Liu, and Ramana V. Davuluri.
  Bioinformatics 37.15 (2021) | code

• LMPred: predicting antimicrobial peptides using pre-trained language models and deep learning [2022]
  Dee, William.
  Bioinformatics Advances 2.1 (2022) | code

• Protein-Protein Interaction Prediction is Achievable with Large Language Models [2023]
  Hallee, Logan, and Jason P. Gleghorn.
  bioRxiv (2023)

• Prediction of virus-host association using protein language models and multiple instance learning [2023]
  Liu, Dan, Francesca Young, David L. Robertson, and Ke Yuan.
  bioRxiv (2023) | code

• Large language models generate functional protein sequences across diverse families [2023]
  Madani, Ali, Ben Krause, Eric R. Greene, Subu Subramanian, Benjamin P. Mohr, James M. Holton, Jose Luis Olmos Jr et al.
  Nat Biotechnol (2023) | code

• On Pre-training Language Model for Antibody [2023]
  Wang, Danqing, Y. E. Fei, and Hao Zhou.
  ICLR (2023) | code

• Efficient evolution of human antibodies from general protein language models [2023]
  Hie, Brian L., Varun R. Shanker, Duo Xu, Theodora UJ Bruun, Payton A. Weidenbacher, Shaogeng Tang, Wesley Wu, John E. Pak, and Peter S. Kim.
  Nat Biotechnol (2023) | code

• AbLang: an antibody language model for completing antibody sequences [2022]
  Olsen, Tobias H., Iain H. Moal, and Charlotte M. Deane.
  Bioinformatics Advances (2022) | code

• Matching Patients to Clinical Trials with Large Language Models [2023]
  Jin, Qiao, Zifeng Wang, Charalampos S. Floudas, Jimeng Sun, and Zhiyong Lu.
  arXiv:2307.15051 (2023)

• ClinicalGPT: Large Language Models Finetuned with Diverse Medical Data and Comprehensive Evaluation [2023]
  Wang, Danqing, Y. E. Fei, and Hao Zhou.
  arXiv:2306.09968v1

• ChemCrow: Augmenting large-language models with chemistry tools [2023]
  Bran, Andres M., Sam Cox, Andrew D. White, and Philippe Schwaller.
  arXiv:2304.05376 (2023) | code

• Large Language Models as Master Key: Unlocking the Secrets of Materials Science with GPT [2023]
  Xie, Tong, Yuwei Wa, Wei Huang, Yufei Zhou, Yixuan Liu, Qingyuan Linghu, Shaozhou Wang, Chunyu Kit, Clara Grazian, and Bram Hoex.
  arXiv:2304.02213v5

• MatSciBERT: A materials domain language model for text mining and information extraction [2022]
  Gupta, Tanishq, Mohd Zaki, NM Anoop Krishnan, and Mausam.
  npj Comput Mater 8, 102 (2022) | code