Find open-source science resources

Transformer architecture for high-energy physics that treats particle jets as unordered sets of constituent particles, using pairwise particle-particle attention to capture interparticle interactions; achieves state-of-the-art jet tagging on the large-scale JetClass benchmark and is widely adopted in LHC flavor-tagging pipelines (Meta FAIR & Penn State, 135+ stars, MIT License, 2023-2024)

Generative model for programmable protein design using diffusion modeling, equivariant graph neural networks, and conditional random fields to efficiently sample diverse all-atom structures; supports conditional generation via composable conditioners for substructure, symmetry, shape, and neural-network predictions; validated crystallographically (Generate Biomedicines, Nature 2023)

Large-scale PDF/LaTeX/JATS parsing to standardized JSON for millions of papers

Circlator is a tool to circularize genome assemblies. It will attempt to identify each circular sequence and output a linearised version of it. It does this by assembling all reads that map to contig ends and comparing the resulting contigs with the input assembly.

Ujjwal Karn.

Content-Aware Image Restoration for Cryo-Transmission Electron Microscopy Data

file format conversion in Biopython in a convenient way.

Open language model for mathematics (7B/34B) trained on Proof-Pile-2, outperforming Minerva at equal scale on MATH benchmark, with tool use and formal theorem proving in Lean without finetuning (EleutherAI, ICLR 2024)

AlphaPickle is a Python tool that converts AlphaFold and ColabFold output files into user-friendly CSV files and plots, enabling easy analysis and visualization of protein prediction data without requiring programming expertise. It processes .pkl, .json, and PDB files to extract and visualize metrics like pLDDT and PAE.

k-mer counting, filtering, and graph traversal.

A package for benchmarking of models for _de novo_ molecular design.

Molecular descriptor calculator based on [RDKit](http://www.rdkit.org/).

Huawei's 3D high-resolution global weather forecast model at 0.25° resolution, first AI method to comprehensively outperform traditional NWP across all variables and lead times, integrated into ECMWF operational forecasts (Nature 2023)

3D Equivariant Diffusion for Target-Aware Molecule Generation (ICLR2023)

Single-cell BERT for gene expression

PINN research collection

OpenChem is a deep learning toolkit for Computational Chemistry with PyTorch backend.

Secure text-to-visualization through standardized chart specifications

DGL-LifeSci is a [DGL](https://www.dgl.ai/)-based package for various applications in life science with graph neural network.

Write-once-read-many table for large datasets.

First foundation model for weather and climate by Microsoft, Vision Transformer-based architecture trained on heterogeneous datasets (ICML 2023)

A VCF Parser for Python.

First vision-and-language foundation model for pathology AI, fine-tuned from CLIP on 249K image-caption pairs, enabling open-ended visual-semantic search and zero-shot diagnosis across histopathology (Pathology Foundation, 376+ stars)

Screen a bacterial assembly (contigs/CDS or proteins) for nucleotide or protein sequences. Pipeline that screens for presence of genes of interest (GOI) in bacterial assemblies. Generates multiple CSVs and plots that describe which genes are present and how variable their sequence is. Can use DNA or protein query sequences (GOIs) and DNA contigs/fastas or protein fastas as database (db) to search in.

DeepDILI is a tool for Deep Learning-Powered Drug-Induced Liver Injury Prediction Using Model-Level Representation

An open, extensible Python framework for GPU-accelerated alchemical free energy calculations.

mtag is a Python-based command line tool for jointly analyzing multiple sets of GWAS summary statistics as described by Turley et. al. (2018). It can also be used as a tool to meta-analyze GWAS results.

Easily submitting PBS jobs with script template. Multiple input files supported.

A Library for Deep Learning in Biology and Chemistry.

A deep learning framework (based on Chainer) with applications in Biology and Chemistry.

Enables machine learning on three-dimensional molecular structure.

NuclearPhaser is a method for phasing of dikaryotic genomes into the two haplotypes using Hi-C contact graphs. This is an overview of the phasing pipeline for dikaryons.

a robust molecular representation learning framework against distribution shifts.

Filtering and trimming of long read sequencing data.

Open Drug Discovery Toolkit, a modular and comprehensive toolkit for use in cheminformatics, molecular modeling etc.

Toolkit for processing molecules, reactions and condensed graphs of reactions. Can be used for chemical standardization, MCS search, tautomers generation with backward compatibility to RDKit and NetworkX.

Go Get Data; A command line interface for obtaining genomic data.

A multimodal deep learning model, DeepNCI, is proposed for improving noncovalent interactions (NCIs) calculated via density functional theory (DFT).

Hierarchical Generation of Molecular Graphs using Structural Motifs.

Learning nonlinear operators

AI for chemical reaction prediction and synthesis planning

Spherical CNNs for astronomy

RepEnrich is a method to estimate repetitive element enrichment using high-throughput sequencing data.

[@crazyhottommy](https://github.com/crazyhottommy)'s notes on various steps and considerations when doing RNA-seq analysis.