AI-based pathology predicts origins for cancers of unknown primary - Nature
- histology
- pathology
- wsi-images
- histopathology
66,762 visible repositories in the index
49–71 of 71 · Most stars
AI-based pathology predicts origins for cancers of unknown primary - Nature
Open source tumor evidence matching for sequencing labs and hospitals without molecular tumor boards. Research prototype; oncologist review required.
ChemML is a machine learning and informatics program suite for the chemical and materials sciences.
The repository host gives no description.
TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020) https://doi.org/10.1093/bioinformatics/btaa524
Safe Bayesian Optimization
Data visualisation web components for the life sciences.
A tool for cell instance aware segmentation in densely packed 3D volumetric images
Auto-QChem is an automated workflow for the generation and storage of DFT calculations for organic molecules.
OCaml Bioinformatics Library
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
Data Access Client for Global Surface Summary of the Day (GSOD) Weather Written in R
TypeDB Bio: Biomedical Knowledge Graph
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
MCP server for spatial transcriptomics analysis through natural language interfaces.
A cheminformatics extension for the SQLAlchemy database toolkit.
Fast, deterministic cell-type deconvolution for million-bin spatial transcriptomics
Java Scientific Computing Library - Signal Processing, FFT, Filters, PSD, DCT, SciPy-like APIs for JVM & Android used in Machine Learning and Data Science.
Workbench for practical machine learning in Ruby.
chemmodlab: A Cheminformatics Modeling Laboratory for Fitting and Assessing Machine Learning Models
UV-first benchmark for protein-ligand docking with reproducible annotation, pocket similarity, and HPC workflows.
Generative models for transcriptomic-driven or protein-driven molecular design (PaccMann^RL).
Simple webapp for generating small ligand conformers