🧰 Open Source Tools — Awesome AI for Science

List of Computer Science courses with video lectures.

Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 160,000+ scientists worldwide. 140 ready-to-use skills plus 100+ scientific databases covering biology, chemistry, medicine, and drug discovery. Compatible with Cursor, Claude Code, Codex, Pi, Antigravity, and the open Agent Skills standard.

Data Apps & Dashboards for Python. No JavaScript Required.

Graph Neural Network Library for PyTorch

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

Python package built to ease deep learning on graph, on top of existing DL frameworks.

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

Official git repository for Biopython (originally converted from CVS)

links to conference publications in graph-based deep learning

A unified, comprehensive and efficient recommendation library

RuVector is a High Performance, Real-Time, Self-Learning Ai, Vector GNN, Memory DB built in Rust.

A library for scientific machine learning and physics-informed learning

A curated list of awesome Bioinformatics libraries and software.

Official repository for the Boltz biomolecular interaction models

SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)

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

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统

A DSL for data-driven computational pipelines

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

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.

StellarGraph - Machine Learning on Graphs

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

Public development project of the LAMMPS MD software package

A distributed graph deep learning framework.

Making Protein folding accessible to all!

An Android app that uses your phone's sensors to assist with wilderness treks or survival situations.

Repository for benchmarking graph neural networks (JMLR 2023)

Single-cell analysis in Python. Scales to >100M cells.

Message Passing Neural Networks for Molecule Property Prediction

Graph Neural Networks with Keras and Tensorflow 2.

An ultra-fast all-in-one FASTQ preprocessor (QC/adapters/trimming/filtering/splitting/merging...)

A versatile pairwise aligner for genomic and spliced nucleotide sequences

MMseqs2: ultra fast and sensitive search and clustering suite

Benchmark datasets, data loaders, and evaluators for graph machine learning

Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

A deep learning package for many-body potential energy representation and molecular dynamics

A full spaCy pipeline and models for scientific/biomedical documents.

Official code repository for GATK versions 4 and up

List of papers about Proteins Design using Deep Learning

OpenMM is a toolkit for molecular simulation using high performance GPU code.

A curated list of Graph/Transformer-based fraud, anomaly, and outlier detection papers & resources

😎 An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.

Conda recipes for the bioconda channel.

CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)

Data intensive science for everyone.

Burrow-Wheeler Aligner for short-read alignment (see minimap2 for long-read alignment)

A curated list of awesome AI tools, libraries, papers, datasets, and frameworks that accelerate scientific discovery — from physics and chemistry to biology, materials, and beyond.

Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).

Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website (https://dlg4nlp.github.io/index.html) for various learning resources!

A curated list of awesome AI tools, libraries, papers, datasets, and frameworks that accelerate scientific discovery — from physics and chemistry to biology, materials, and beyond.

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations

MDAnalysis is a Python library to analyze molecular dynamics simulations.

A powerful and flexible machine learning platform for drug discovery

A cross-platform and ultrafast toolkit for FASTA/Q file manipulation

A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods