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Foundation model for universal prompt-driven medical image segmentation extending SAM3 to clinical imaging, supporting 2D public benchmarks and 3D training/evaluation with text and box prompts; pretrained weights available on HuggingFace (189+ stars)

Numerical differential equation solving in JAX

Burrow-Wheeler Aligner for pairwise alignment between DNA sequences.

This Hugging Face repository stores the official resources for RAMER (reaction-aware multimodal enzyme function representation model).

The scECODA R package provides a complete workflow for the analysis and visualization of compositional data, primarily focusing on cell type proportions derived from single-cell data. It implements specialized methods, such as the Centered Log-Ratio (CLR) transformation, to properly analyze proportional data while avoiding the biases introduced by the compositional constraint. The package encapsulates data management, transformation, and analysis into a single SummarizedExperiment object, offering downstream tools for dimensionality reduction via PCA, calculating critical metrics like the Adjusted Rand Index (ARI) and Modularity to quantify sample grouping quality, and generating high-quality visualizations like heatmaps and scatter plots.

ProtGPT3-MSA is a multiple-sequence, homolog-conditioned autoregressive protein language model. It is part of the ProtGPT3 family, an open-source suite of promptable and aligned protein language models for protein sequence generation.

DenoIST identifies and removes contamination in Image-based Spatial Transcriptomics data, using a transposed poisson mixture model with local neighbourhood offsets to infer genes that are likely to be due to neighbourhood contamination rather than endogenous expression.

Arc Institute's 40B-parameter genome foundation model trained on 9 trillion nucleotides from all domains of life, supporting 1M base pair context for generalist DNA/RNA/protein prediction and design (Nature 2026)

KAU-BioMedLLM is a research prototype for source-grounded biomedical variant interpretation. The current public release contains the LoRA adapter and documentation for a guarded report-generation system built around a curated biomedical evidence panel, citation enforcement, and abstention when…

Stack is a large-scale encoder-decoder foundation model for single-cell biology. It introduces a novel tabular attention architecture that enables both intra- and inter-cellular information flow, setting cell-by-gene matrix chunks as the basic input data unit.

A single molecule sequence assembler for genomes large and small.

The submission-centric metadata schema for the German Human Genome-Phenome Archive (GHGA).

MeLSI (Metric Learning for Statistical Inference) is a novel machine learning method for microbiome data analysis that learns optimal distance metrics to improve statistical power in detecting group differences. Unlike traditional distance metrics (Bray-Curtis, Euclidean, Jaccard), MeLSI adapts to the specific characteristics of your dataset to maximize separation between groups. The method uses an ensemble of weak learners to identify which microbial features drive group differences, providing both improved statistical power and biological interpretability through feature importance weights.

Have you ever index sorted cells in a 96 or 384-well plate and then sequenced using Sanger sequencing? If so, you probably had some struggles to either check the electropherogram of each cell sequenced manually, or when you tried to identify which cell was sorted where after sequencing the plate. Scifer was developed to solve this issue by performing basic quality control of Sanger sequences and merging flow cytometry data from probed single-cell sorted B cells with sequencing data. scifer can export summary tables, 'fasta' files, electropherograms for visual inspection, and generate reports.

This model is an NF4 (Normal Float 4-bit) quantized version of the base model InstaDeepAI/nucleotide-transformer-2.5b-multi-species. The checkpoint was quantized using the BitsAndBytes library with double quantization enabled and BF16 computation.

A multitude of tools for comparative genomics, focused on large-scale analyses of biological data. SynExtend includes tools for working with syntenic data, clustering massive network structures, and estimating functional relationships among genes.

Fudan University's cascade machine learning forecasting system for 15-day global weather prediction, employing a 3D Earth-specific transformer with hard-constraint techniques to achieve state-of-the-art accuracy against traditional NWP and AI baselines

Diffusion-based document OCR framework replacing autoregressive decoding with block-level parallel diffusion decoding, enabling high-accuracy text recognition in scientific PDFs (613+ stars, MIT License)

Genome-wide association studies (GWAS) are widely used to investigate the genetic basis of diseases and traits, but they pose many computational challenges. We developed an R package SNPRelate to provide a binary format for single-nucleotide polymorphism (SNP) data in GWAS utilizing CoreArray Genomic Data Structure (GDS) data files. The GDS format offers the efficient operations specifically designed for integers with two bits, since a SNP could occupy only two bits. SNPRelate is also designed to accelerate two key computations on SNP data using parallel computing for multi-core symmetric multiprocessing computer architectures: Principal Component Analysis (PCA) and relatedness analysis using Identity-By-Descent measures. The SNP GDS format is also used by the GWASTools package with the support of S4 classes and generic functions. The extended GDS format is implemented in the SeqArray package to support the storage of single nucleotide variations (SNVs), insertion/deletion polymorphism (indel) and structural variation calls in whole-genome and whole-exome variant data.

DCAT-AP is a DCAT profile for sharing information about Catalogues containing Datasets and Data Services descriptions in Europe, under maintenance by the SEMIC action, Interoperable Europe. This Application Profile provides a minimal common basis within Europe to share Datasets and Data Services cross-border and cross-domain. [from homepage]

pairedGSEA makes it simple to run a paired Differential Gene Expression (DGE) and Differencital Gene Splicing (DGS) analysis. The package allows you to store intermediate results for further investiation, if desired. pairedGSEA comes with a wrapper function for running an Over-Representation Analysis (ORA) and functionalities for plotting the results.

Gene expression prediction

DANTE is a software tool for genotyping and characterizing tandem repeats (TRs) from both second- and third-generation sequencing data. It supports the analysis of short-read massively parallel sequencing (sr-MPS) and long-read massively parallel sequencing (lr-MPS), enabling accurate repeat characterization across a wide range of loci. A key feature of DANTE is its ability to determine genotypes at nucleotide resolution, including the characterization and phasing of complex repeat motifs. For sr-MPS data, the tool determines allele size and sequence composition of alleles for which spanning reads are generated. In addition, it identifies alleles that exceed the sequencing read length by estimating their presence from partial read evidence and supports the visualisation of the sequence composition of partial reads. For lr-MPS data, where complete repeat regions are typically sequenced, DANTE determines the allele size and sequence composition of identified alleles.

GraphExperiment provides users and developers with an S4 class that extends `SingleCellExperiment` by offering infrastructure to store and retrieve networks (`igraph` objects) representing how assay features and/or observations are associated with each other. The class was designed to store networks inferred from high-dimensional quantitative data, with feature-feature networks including gene coexpression networks (GCNs), gene regulatory networks (GRNs), and co-abundance networks (from proteomics and metabolomics), and observation-observation network including cell-cell distances, species-species relationships, and sample-sample similarities.

> [!WARNING] > This is a model trained on publicly available data. While we've done our best to curate the data, the model performance can still improve. Proceed with caution.

Annotate a VCF with other VCFs/BEDs/tabixed files.

Provides C and C++ hdf5 libraries.

The NCBI Gene Expression Omnibus (GEO) is a public repository of microarray data. Given the rich and varied nature of this resource, it is only natural to want to apply BioConductor tools to these data. GEOquery is the bridge between GEO and BioConductor.

SPAdes (St. Petersburg genome assembler) is an assembly toolkit containing various assembly pipelines and the de-facto standard for prokaryotic genome assemblies.

## Important Notice If you are using GENERator for sequence generation, please ensure that the length of each input sequence is a multiple of 6. This can be achieved by either: 1. Padding the sequence on the left with 'A' (left padding); 2. Truncating the sequence from the left (left truncation).

Cross-platform system optimizations for accelerating AlphaFold3 training with 1.73x speedup and 1.23x memory reduction

 

 

 

 

Minimalist, batteries-included repository for training video world models with diffusion-forcing, supporting long-horizon rollouts, 3D point-cloud generation, and model-predictive control with pretrained checkpoints (Simchowitz Lab, 700+ stars, MIT License, 2026)

Back to basics: Observed statistics are sufficient to predict drug responses

Learning the language of protein-protein interactions

Genomic foundation model for metagenomic and genome annotation, featuring an 8k base-pair context and 500M parameters trained on 386B base pairs of eukaryotic DNA; provides expert models and a unified CLI for prokaryotic/eukaryotic coding-sequence annotation with strong performance on Genomic Benchmarks, Nucleotide Transformer tasks, and custom Gener tasks (GenerTeam, 314+ stars, MIT License)

Automatic atomic model building program for cryo-EM maps using deep learning, enabling rapid de novo protein structure determination from electron density with high accuracy (3DEM/EMBL, 169+ stars)

Performs laboratory unit conversions across molarity, OD600 cell density, C₁V₁ dilution, and related dimensional pairs from mass, volume, molecular weight, and organism-specific OD factors. A browser calculator combines four modes in one tabbed workspace with compound MW lookup, species-aware OD uncertainty ranges, cross-tab chaining, and shareable links; a Python library and command-line tool submit the same parameters to the Pepkio Tools API for scripted use. Calculator arithmetic for the API client is hosted remotely; the client transmits conversion inputs and returns structured results and shareable run identifiers.

Functions helpful for LIBD deconvolution project. Includes tools for marker finding with mean ratio, expression plotting, and plotting deconvolution results. Working to include DLPFC datasets.

!IntelliFold Cover

Translates spectrophotometer and NanoDrop readings into mass and molar concentrations for dsDNA, ssDNA, ssRNA, and protein from a single anchor input, with optional sequence-specific nearest-neighbor extinction coefficients. A browser calculator supports bidirectional unit conversion, batch processing of up to ninety-six NanoDrop export rows, and A260/A280 purity interpretation with plain-language warnings; a REST API exposes converter, batch, and purity modes for scripted use. Calculator arithmetic is hosted remotely; API clients transmit parameters and return structured result fields and shareable run identifiers.

Calculates sequence-derived molecular properties and related laboratory planning outputs from FASTA and assay setup inputs. The tool supports sequence analysis for DNA, RNA, and protein entries, plus dilution and ligation calculation modes through one API-backed workflow. Programmatic use is available through a Python library and command-line interface that submit run payloads and return structured result objects.