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List of latest/classical papers about AI for Biology. Beginning in 2023. Present emphasis on Protein.

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AI for Biology - Paper Reading List

This curated reading list focuses on the intersection of AI and biology, offering a selection of key papers and resources. Currently includes the following areas:

  • Protein 🔥
  • Foundation models 🔥
    • Large deep learning models for biology (e.g., biomolecule, biomedical, ...)
  • Others
    • unclassified yet (e.g., RNA, BioText, ...)

🚀 This list is currently collected manually in tabular form:

Tag Title Pub.&Year Notes
[Survey] / [Benchmark] / Abbreviation Paper title e.g., bioRxiv '2024 code, blog, or some important notes

🚀 A glimpse into AI4Science: Scientific discovery in the age of artificial intelligence (Nature '2023)

Protein

Topic What's it about?
Immunity-related HLA, T-cell receptor (TCR), Antibody, Antigen, ...
Protein representation Protein Language model, structure representation, ...
Protein meets LLM After the emergence of ChatGPT
Protein design Design protein sequence
Structure prediction Sequence to structure, AlphaFold and its applications
Protein interaction Protein-protein/ligand interaction, Docking
[To be updated]

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Foundation models

Title Pub.&Year Notes
[Survey] Leveraging Biomolecule and Natural Language through Multi-Modal Learning: A Survey Arxiv '2024
[Survey] Foundation Model for Advancing Healthcare: Challenges, Opportunities, and Future Directions Arxiv '2024 pape list
BioBridge BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs ICLR '2024 code

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Others

Title Pub.&Year Notes
Geneformer Transfer learning enables predictions in network biology Nature '2023
CancerGPT CancerGPT: Few-shot Drug Pair Synergy Prediction using Large Pre-trained Language Models npj Digital Medicine '2024

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List of latest/classical papers about AI for Biology. Beginning in 2023. Present emphasis on Protein.

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