biomedicine

Biomni: a general-purpose biomedical AI agent

Therapeutics Commons (TDC): Multimodal Foundation for Therapeutic Science

精选了10K+项目，包括机器学习、深度学习、NLP、GNN、推荐系统、生物医药、机器视觉、前后端开发等内容。Selected more than 10k+ projects, including machine learning, deep learning, NLP, GNN, recommendation system, biomedicine, machine vision, etc. Let more excellent projects be discovered by people. Continue to update! Welcome to star!

Automated Modelling for Biological Evidence-based Research

🧬 o r t h o g e n e 🧬✨✨✨✨✨✨✨ Interspecies gene mapping✨✨✨✨✨ 🦠 🔁 🌱 🔁 🌳 🔁 🍎 🔁 🍊 🔁 🪱 🔁 🪰 🔁 🐟 🔁 🦎 🔁 🐓 🔁 🦇 🔁 🐄 🔁 🐖 🔁 🐐 🔁 🐎 🔁 🐈 🔁 🐕 🔁 🐁 🔁 🐒 🔁 🦧 🔁 🦍 🔁 🏃‍♀️

This repository stores the OWL ontology built on the basis of the ISO standards for identification of medicinal products.

PlaNet: Predicting population response to drugs via clinical knowledge graph

This project is done for the Biomedicine, Biotechnology and Public Healthcare department of the University of Cádiz. They idea is to automatize the processing of the microscopic images of their experiments related to angiogenesis.

This is a curated list of tutorials, projects, libraries, videos, papers, books and anything related to applications of Deep Learning to biomedicine. Feel free to make a pull request to contribute to this list.

APRILE: A python library for exploring Adverse Polypharmacy Reaction using Intelligent Learner and Explainer

Virtual laboratory for rational drug design and discovery at the blood-brain barrier supervised by Prof. Dr. Sergey Shityakov from Wuerzburg University, Germany

Multi-Scale Target Explorer systematically identifies, prioritises, and visualises cell-type-specific gene therapy targets across the phenome.

The answers to the assignment of the Wireless Sensor Netwoeks course as taught in the Electrical and Computer Engineering Department of the Aristotle University in 2019.

Import and analyse large-scale biomedical knowledge graphs and ontologies. 🕸️⚙️💻⚙️🕸️

Analyzed 20k+ PubMed abstracts on intestinal organoids using NLP (topic modeling, embeddings, clustering) to uncover research trends.

This project illustrates a comprehensive framework for analysing clinical trial data with minimal code in R using a variety of statistical methods and metrics, as well as various data visualisations.

Automatically uncover Interesting (novel, plausible, and useful) features in biomedical data by combining statistical filtering, literature mining, knowledge graphs and LLMs on UK BioBank tabular features

Repositiory for code used in "Nutritional dependence of sperm mitochondrial metabolism and small RNA biogenesis"

A large dataset for studying the early readmission of diabetic patients problem

endogene.bio’s research platform helps discover molecular biomarkers to better diagnose and stratify patients, and to improve drug discovery processes using menstrual blood. The company work with analytical laboratories to provide diagnostic tests and we assist pharmaceutical companies in optimizing drug development and patient stratification...