Bioinformatics
Showing 36 of 203 projects
A curated collection of papers, datasets, tools, and resources for applying machine learning to small-molecule drug discovery.
An open and extensible Fiji plugin for single-particle tracking in life-science microscopy images.
Open-source software and data format standards for storing and manipulating biological light microscopy data.
An R package to interact with NCBI's Entrez system, enabling programmatic search and retrieval of biological data.
A Python library for blazing-fast, memory-efficient genomics data operations using DataFrames.
A PyTorch-based segmentation toolbox for electron microscopy connectomics, enabling neural structure analysis in 3D volumes.
A probabilistic cell segmentation method for spatial transcriptomics data from platforms like Xenium, CosMx, MERSCOPE, and Visium HD.
A computational pipeline that predicts drug-target interactions by learning low-dimensional vector representations from heterogeneous biological networks.
A Python package for easy molecular docking with a curated dataset and benchmark tasks for drug discovery.
A Python API for downloading and processing neuroanatomical atlas data from multiple sources.
An R package to programmatically retrieve chemical information from various web databases and APIs.
A Julia package providing core utilities for manipulating, comparing, and analyzing phylogenetic trees and networks.
A resource and evaluation framework for benchmarking link prediction models on large-scale, heterogeneous biomedical knowledge graphs.
A large transformer foundation model for single-cell RNA sequencing data analysis, including gene network inference, denoising, and cell annotation.
A conversational AI framework for editing small molecules, peptides, and proteins using retrieval-augmented generation and domain feedback.
An R package for visualizing, adjusting, and comparing hierarchical clustering dendrograms.
A curated collection of databases, software, and papers for computational biology research.
A deep learning model using transformer architecture to predict compound-protein interactions from molecular and protein sequences.
A deep bilinear attention network framework with adversarial domain adaptation for interpretable drug-target interaction prediction.
A collection of reusable web components for visualizing biological data like protein sequences and features.
A Python package for processing and normalizing high-dimensional morphological feature data from high-throughput cell imaging experiments.
A benchmark suite of protein sequence tasks to evaluate machine learning models for protein design.
A Python library for interacting with QuPath, providing a pythonic interface to manage and analyze digital pathology projects.
A tool for cell instance aware segmentation in densely packed 3D volumetric images, originally developed for plant tissues.
A scikit-learn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.
A knowledge-informed cross-species foundation model pre-trained on over 120 million human and mouse single-cell transcriptomes to decipher universal gene regulatory mechanisms.
A high-performance, user-friendly OCaml library for bioinformatics applications.
A deep learning framework for predicting chromatin profiles and sequence regulatory activities from DNA sequences and variants.
A functional bioinformatics library for Scala providing strongly-typed DNA/RNA/protein sequences, transcription, translation, and alignment utilities.
An open-source ImageJ plugin for automated processing, analysis, and visualization of single molecule localization microscopy (SMLM) data.
A suite of tools (wham and whamg) for sensitive and accurate structural variant detection and association testing from genomic sequencing data.
Rust edit distance library accelerated with SIMD for fast Hamming, Levenshtein, and Damerau-Levenshtein calculations.
A curated list of resources for molecular docking, protein-protein docking, and related computational biology tasks.
A pre-trained language model for single-cell RNA sequencing data that encodes cell-cell relations and accelerates inference for downstream tasks.
A performant JAX reimplementation of the UniRep model for generating protein sequence representations.
A Python library for learning Bayesian network structure from observational and interventional data with support for missing values and parallel execution.
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