Awesome Protein Representation Learning

[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

Janus-Series: Unified Multimodal Understanding and Generation Models

Protein-Ligand Interaction Profiler - Analyze and visualize non-covalent protein-ligand interactions in PDB files according to 📝 Adasme et al. (2021), https://doi.org/10.1093/nar/gkab294

Region-Aware Text-to-Image Generation via Hard Binding and Soft Refinement 🔥

List of papers about Proteins Design using Deep Learning

Rifdock Library for Conformational Search

For protein superfamily sequence profile alignment and curation.

AlphaFold 3 inference pipeline.

从零手搓Flow Matching（Rectified Flow）

A summary of related works about flow matching, stochastic interpolants

Let your Claude able to think

Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2

Geometric deep learning of protein–DNA binding specificity

code to run EPInformer for gene expression prediction and gene-enhancer links prioritization

InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models

Contrastive learning of structure-activity relationship

Jigsaw-like AggMap: A Robust and Explainable Multi-Channel Omics Deep Learning Tool

Papers about Structure-based Drug Design (SBDD)

Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.

The simplest, fastest repository for training/finetuning medium-sized GPTs.

A Collection of Variational Autoencoders (VAE) in PyTorch.

Python code for paper - Variational Deep Embedding : A Generative Approach to Clustering

Benchmarking computational single cell ATAC-seq methods

MDM