plantiSMASH

Open-source LLM-powered R&D agent framework automating data-driven AI solution building through automated research, development, and evolution; achieves top open-source performance on MLE-Bench with dual Researcher-Developer agents and supports research copilot, data mining, Kaggle, and quant R&D workflows (13.6K+ stars, MIT License, 2025-2026)

Library of descriptors to aid in the data-mining of materials properties, created by the Lawrence Berkeley National Laboratory.

Bias factorized, base-resolution deep learning models of chromatin accessibility (chromBPNet).

Nallo is a bioinformatics analysis pipeline for long-reads from both PacBio and (targeted) ONT-data, focused on rare-disease. The pipeline detects a wide range of genetic variants, performs genome assembly, and reports CpG methylation. It also enables annotation and ranking of variants based on their predicted functional consequences.

Predicts transcription factor binding sites in up to 316 vertebrate species by scoring JASPAR matrices against Ensembl promoter sequences and combining the match with seven contextual experimental datapoints, including evolutionary conservation, CAGE-defined transcription start sites, eQTLs, ChIP-seq peaks, ATAC-seq accessibility, DNase footprints and gene expression correlation, into a single score per site.

Digital Expression Explorer 2 (or DEE2 for short) is a repository of processed RNA-seq data in the form of counts. It was designed so that researchers could undertake re-analysis and meta-analysis of published RNA-seq studies quickly and easily. As of April 2020, over 1 million SRA datasets have been processed. This package provides an R interface to access these expression data. More information about the DEE2 project can be found at the project homepage (http://dee2.io) and main publication (https://doi.org/10.1093/gigascience/giz022).