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Scientific Large Language Models: A Survey on Biological & Chemical Domains
| Date | Stars |
|---|---|
| 2026-07-31 | 359 |
| 2026-08-02 | 359 |
| 2026-08-06 | 359 |
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# Scientific Large Language Models (Sci-LLMs)
This repository collects papers on scientific large language models, particularly in the domains of biology and chemistry.
> 😎 Welcome to recommend missing papers through **`Adding Issues`** or **`Pull Requests`**.
## 🔔 News
- 💥 [2025/08]Our work **[SciToolAgent](https://github.com/HICAI-ZJU/SciToolAgent)** has been accepted by **Nature Computational Science**. It is a powerful agent framework designed to integrate diverse scientific tools with LLMs.
- 💥 [2025/07]Our work **[InstructBioMol](https://github.com/HICAI-ZJU/InstructBioMol)** has been accepted by **Nature Machine Intelligence**. It is a large language model that enables any-to-any alignment between biomolecules and natural language.
- 💥 [2024/07] We have updated our survey paper by incorporating the latest related works. Please refer to the revised version on [arXiv](https://arxiv.org/abs/2401.14656/v2).
- 💥 [2024/01] Our survey paper 'Scientific Large Language Models: A Survey on Biological & Chemical Domains' has been released on [arXiv](https://arxiv.org/abs/2401.14656/v1).

In this survey, we focus on scientific languages (i.e., textual, molecular, protein and genomic languages), as well as their combination (i.e., multimodal language).
## 🌟 Contents
- [Scientific Large Language Models (Sci-LLMs)](#scientific-large-language-models-sci-llms)
- [🔔 News](#-news)
- [🌟 Contents](#-contents)
- [📖 Textual Scientific Large Language Models (Text-Sci-LLMs)](#-textual-scientific-large-language-models-text-sci-llms)
- [Medical](#medical)
- [Biology](#biology)
- [Chemistry](#chemistry)
- [Comprehensive](#comprehensive)
- [Datasets and Benchmarks](#datasets-and-benchmarks)
- [🧪 Molecular Large Language Models (Mol-LLMs)](#-molecular-large-language-models-mol-llms)
- [Molecule Property Prediction](#molecule-property-prediction)
- [Interaction Prediction](#interaction-prediction)
- [Molecule Generation/Design/Edit](#molecule-generationdesignedit)
- [Reaction Prediction](#reaction-prediction)
- [Datasets and Benchmarks](#datasets-and-benchmarks-1)
- [🧬 Protein Large Language Models (Prot-LLMs)](#-protein-large-language-models-prot-llms)
- [Protein Sequence Representation](#protein-sequence-representation)
- [Protein Sequence Generation/Design](#protein-sequence-generationdesign)
- [Datasets and Benchmarks](#datasets-and-benchmarks-2)
- [🦠 Genomic Large Language Models (Gene-LLMs)](#-genomic-large-language-models-gene-llms)
- [General](#general)
- [Function Prediction](#function-prediction)
- [Variants and Evolution Prediction](#variants-and-evolution-prediction)
- [DNA-Protein Interaction Prediction](#dna-protein-interaction-prediction)
- [RNA Prediction](#rna-prediction)
- [Datasets and Benchmarks](#datasets-and-benchmarks-3)
- [Ⓜ️ Multimodal Scientific Large Language Models (MM-Sci-LLMs)](#️-multimodal-scientific-large-language-models-mm-sci-llms)
- [Molecule\&text](#moleculetext)
- [Protein\&text](#proteintext)
- [Protein\&molecule](#proteinmolecule)
- [Cell\&Text](#celltext)
- [Comprehensive](#comprehensive-1)
- [Datasets and Benchmarks](#datasets-and-benchmarks-4)
- [Molecule\&Text](#moleculetext-1)
- [Protein\&Text](#proteintext-1)
- [Protein\&Molecule](#proteinmolecule-1)
- [Cell\&Text](#celltext-1)
- [Comprehensive](#comprehensive-2)
- [👥 Contributions](#-contributions)
- [Citation](#citation)
- [Contributors](#contributors)
- [Contact](#contact)
## 📖 Textual Scientific Large Language Models (Text-Sci-LLMs)
### Medical
- `2019.04` ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission, [arXiv](https://arxiv.org/abs/1904.05342), [Code](https://github.com/kexinhuang12345/clinicalBERT)
- `2022.02` GatorTron: A Large Clinical Language Model to Unlock Patient Information from UnstructExcerpt of 77,238 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:3047071e86a3fada, topic:large-language-models
matched fp:3047071e86a3fada, topic:multimodal