ProtLLM

[Aspirit]

Description:
ProtLLM is a protein-focused large language model (LLM) designed to bridge natural language processing (NLP) with protein sequence understanding. The model is trained using an interleaved protein-language approach, meaning it processes both textual data and protein sequences in a unified way. ProtLLM is particularly useful for functional protein annotation, structure prediction, and AI-driven molecular discovery, making it a valuable tool for bioinformatics and protein engineering.

Key Features:

Interleaved Protein-Language Model: Integrates protein sequences and natural language representations.
Pretrained on Large-Scale Datasets: Optimized for protein annotation, molecular function prediction, and bioinformatics tasks.
Supports Protein-Language Alignment: Enhances sequence-based reasoning and functional interpretation.
Applications: Computational protein design, synthetic biology, AI-driven drug discovery, and molecular function annotation.

[Aspirit]

Publication:
📄 ProtLLM: An Interleaved Protein-Language LLM with Protein-as-Word Pre-Training
🔗 Read the Paper​

Code Source:
📂 GitHub Repository: ProtLLM on GitHub​
📂 Model Download: ProtLLM on Hugging Face​

[Aspirit]

This forum topic is for bioinformaticians, AI researchers, and protein engineers interested in ProtLLM. Join this discussion to:

Learn how ProtLLM integrates protein sequences with NLP models.
Discuss fine-tuning techniques for protein structure and function prediction.
Explore real-world applications in synthetic biology and AI-driven drug discovery.
Collaborate on enhancing ProtLLM’s capabilities for molecular function annotation.
🚀 Join us in advancing AI-driven protein sequence modeling with ProtLLM!

[Author]

Posts