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code for SeqDance/ESMDance, biophysics-informed protein language models
bert-loves-chemistry: a repository of HuggingFace models applied on chemical SMILES data for drug design, chemical modelling, etc.
Papers about Structure-based Drug Design (SBDD)
Code release for "LogME: Practical Assessment of Pre-trained Models for Transfer Learning" (ICML 2021) and Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs (JMLR 2022)
DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.
A toolkit for optimal workflow recommendation for proteomics data differential expression analysis
Homomer symmetry prediction from protein sequence
Proteina is a new large-scale flow-based protein backbone generator that utilizes hierarchical fold class labels for conditioning and relies on a tailored scalable transformer architecture.
Official open-source of Antibody Design Using a Score-based Diffusion Model Guided by Evolutionary, Physical, and Geometric Constraints
🏭 Easy data acquisition, benchmark resources, PLM fine-tuning for bio-researchers.
A Protein Large Language Model for Generate Nanobody Sequences
Versatile Embedding Network for Understanding protein Sequences
Protein hallucination and inpainting with RoseTTAFold
Protein function prediction using protein structures and deep graph neural networks.
Generative Models for Graph-Based Protein Design
Implementation of trRosetta and trDesign for Pytorch, made into a convenient package, for protein structure prediction and design
A package to predict protein inter-residue geometries from sequence data
List of papers about Proteins Design using Deep Learning
Evolutionary Scale Modeling (esm): Pretrained language models for proteins
Code for ICML 2024 paper "Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning"