protein-embedding

Awesome Protein Representation Learning

Source code for "Learning protein sequence embeddings using information from structure" - ICLR 2019

Code for ICLR 2024 (Spotlight) paper "MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding"

Multi-task and masked language model-based protein sequence embedding models.

Published in PLOS ONE. Phage-host interaction prediction tool that uses protein language models to represent the receptor-binding proteins of phages. It presents improvements over using handcrafted sequence properties and eliminates the need to manually extract and select features from phage sequences

Simple python interface for the OpenProtein.AI REST API.

Published in Bioinformatics. Phage-host interaction prediction tool that incorporates protein structure information in representing receptor-binding proteins (RBPs). It improves performance especially for phages with RBPs that have low sequence similarity to those of known phages

Generation Co-expression Network Embeddings (CxNEs) for plant genes using Graph Attention Networks (GAT))

🎛️ Enhance your Common Lisp experience with ICL, an interactive REPL offering modern features like readline editing, tab completion, and persistent history.

🧬 AI Drug Discovery Simulator — Generate protein embeddings, create drug-like molecules, predict binding affinity, analyze ADMET properties, and rank candidates using ESM-2, RDKit, Groq, and Streamlit.