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First architecture deeply integrating a DNA foundation model with an LLM for multimodal biological reasoning, achieving 98% accuracy on KEGG disease pathway prediction and 15%+ average gains on variant effect prediction with interpretable step-by-step reasoning traces (bowang-lab, 390+ stars)

A toolkit for simulating differential microbiome data designed for longitudinal analyses. Several functional forms may be specified for the mean trend. Observations are drawn from a multivariate normal model. The objective of this package is to be able to simulate data in order to accurately compare different longitudinal methods for differential abundance.

First system to make novel, verifiable scientific discoveries by pairing LLMs with evolutionary search, solving open problems in combinatorics (cap set problem) and discovering faster matrix multiplication algorithms

Universal medical image segmentation foundation model trained on 1.57M image-mask pairs across 10 imaging modalities and 30+ cancer types (Nature Communications 2024)

Provides functionality for producing geometric representations of protein and RNA structures, and biological interaction networks.

Babelon is a simple standard for managing ontology translations and language profiles. Profiles are managed as TSV files, see for example https://github.com/obophenotype/hpo-translations/tree/main/babelon. The goal of Babelon as a data model and vocabulary is to capture the minimum data required to capture important metadata such as confidence and precision of translation.

This ontology models classes and relationships describing deep learning networks, their component layers and activation functions, as well as potential biases.