VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning
Natural language processing (NLP) has significantly influenced scientific domains beyond human language, including protein engineering, where pre-trained protein language models (PLMs) have demonstrated remarkable success. However, interdisciplinary adoption remains limited due to challenges in data collection, task benchmarking, and application. This work presents VenusFactory, a versatile engine that integrates biological data retrieval, standardized task benchmarking, and modular fine-tuning of PLMs. VenusFactory supports both computer science and biology communities with choices of both a command-line execution and a Gradio-based no-code interface, integrating $40+$ protein-related datasets and $40+$ popular PLMs. All implementations are open-sourced on https://github.com/tyang816/VenusFactory.
Code (1)
Tasks
BenchmarkingLanguage ModelingLanguage ModellingRetrievalSimilar Papers 제목 키워드 기반
Self-evolving AI agents for protein discovery and directed evolution
Protein scientific discovery is bottlenecked by the manual orchestration of information and algorithms, while general agents are insufficient in complex domain projects. VenusFactory2 provides an autonomous framework tha…
TourSynbio-Search: A Large Language Model Driven Agent Framework for Unified Search Method for Protein Engineering
The exponential growth in protein-related databases and scientific literature, combined with increasing demands for efficient biological information retrieval, has created an urgent need for unified and accessible search…
Information RetrievalLanguage ModelingLanguage ModellingLarge Language Model+3The Protein Engineering Tournament: An Open Science Benchmark for Protein Modeling and Design
The grand challenge of protein engineering is the development of computational models that can characterize and generate protein sequences for any arbitrary function. However, progress today is limited by lack of 1) benc…
BenchmarkingProteinEngine: Empower LLM with Domain Knowledge for Protein Engineering
Large language models (LLMs) have garnered considerable attention for their proficiency in tackling intricate tasks, particularly leveraging their capacities for zero-shot and in-context learning. However, their utility …
In-Context LearningProtein DesignProtein Function PredictionESM All-Atom: Multi-scale Protein Language Model for Unified Molecular Modeling
Protein language models have demonstrated significant potential in the field of protein engineering. However, current protein language models primarily operate at the residue scale, which limits their ability to provide …
AllLanguage ModelingLanguage ModellingProtein Language Model