Awesome-LLMs-meet-genomes

Awesome-LLMs-meet-genomes is a collection of state-of-the-art, novel, exciting LLMs methods on genomes. It contains papers, codes, datasets, evaluations, and analyses. Any additional information about LLMs for bioinformatics is welcome, and we are glad to add you to the contributor list here. Any problems, please contact yangchengyjs@163.com. If you find this repository useful to your research or work, it is really appreciated to star this repository. ✨

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Table of Content

• Awesome-LLMs-meet-genomes
  • Sponsor
  • Table of Content
  • 🔔 News
  • Important Survey Papers
  • Important Benchmarks
  • Genomic Large Language Models (Gene-LLMs)
    • Generic Base Models
    • DNA Sequence Design
    • DNA Multimodal
    • RNA Foundation Models
    • Sequence-to-Function
    • Sequence-to-Expression
    • Downstream Tasks
      • Gene Pathogenicity Prediction
      • Retrieval-Augmented Generation
      • Function Prediction
      • Perturbation
      • Variants and Evolution Prediction
      • Fine-tuning for Genomes and proteins
      • Interaction Prediction
      • Identification of Transcription Factor Binding Sites
      • Origins of Replication Rite Prediction
      • DNA-binding Protein Prediction
      • RNA Prediction
      • Sequence Modeling
      • Reinforcement learning
      • Evolution
  • Basics of Sequence Modeling
  • Tokenization
  • Position Code
  • Adversarial Attack
  • Quantization
  • Fine-tuning
  • Reducing Knowledge Hallucination
  • Data processing
  • Other Related Awesome Repository
  • Contributors

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🔔 News

• 🧬✔️ [2024/09] Benchmarks for classification of genomic sequences link.
• 💥 [2024/08] Some real-world experience in training LLMs link.
• 💥 [2024/08] Three ways of Fine-tuning link.
• 💥 [2024/08] Visualisation of the Transformer Principle link.
• 🌟 [2024/08] The Cultivation Method of Large Language Models: A Path to Success link.
• 📖 [2024/08] Large Language Models: From Theory to Practice link.

Important Survey Papers

Important Benchmarks

Genomic Large Language Models (Gene-LLMs)

Generic Base Models

DNA Sequence Design

DNA Multimodal

RNA Foundation Models

Sequence-to-Function

Sequence-to-Expression

Downstream Tasks

Gene Pathogenicity Prediction

Retrieval-Augmented Generation

Function Prediction

Perturbation

Variants and Evolution Prediction

Fine-tuning for Genomes and proteins

Interaction Prediction

Identification of Transcription Factor Binding Sites

Origins of Replication Rite Prediction

DNA-binding Protein Prediction

RNA Prediction

Sequence Modeling

Reinforcement learning

Evolution

Basics of Sequence Modeling

Tokenization

Position Code

Adversarial Attack

Quantization

Fine-tuning

Reducing Knowledge Hallucination

Data processing

1、从 FASTA 文件中加载并查询基因组序列.
2、DNABERT2 Fine-Tuning for DHS Specificity Prediction.
3、Scaling-Laws-of-Genomic.
4、Deafness-mutation-sites.
5、DNABERT-2_CNN_BiLSTM.
6、1_Train_HG.
7、dbtk-dnabert.
8、DNABERT2_Tokenizer.
9、处理序列的R脚本.

Other Related Awesome Repository

1. Awesome-LLM-Learning
2. Scientific-LLM-Survey (Biological & Chemical Domains)
3. LLM-FineTuning-Large-Language-Models
4. Awesome-llms-fine-tuning (Explore a comprehensive collection of resources, tutorials, papers, tools, and best practices for fine-tuning Large Language Models (LLMs))
5. Awesome-LLM4RS-Papers
6. LLM4Rec-Awesome-Papers (A list of awesome papers and resources of recommender system on large language model (LLM))
7. Awesome-Code-LLM (A curated list of language modeling researches for code and related datasets)

Contributors

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