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Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks

OmicsOracle is an integrated platform that synthesizes natural language processing with biomedical knowledge graphs, enabling researchers to query complex biomedical data using simple language and receive comprehensive, AI-interpreted results.

The phenome_outlier_analysis package offers tools for detecting outliers in large-scale phenomic datasets, supporting both context-specific and global strategies to enhance biological insight discovery in high-dimensional omics research.

This package contains a series of utility functions designed to process and analyze Arivale data, including metabolomics, proteomics, and client information.

OmicsForge: An R package for efficient multi-omics data processing. Streamlines loading, cleaning, aggregating, filtering, and imputing missing values in proteomics and metabolomics datasets. Supports both longitudinal and baseline studies.

This repository contains code associated with the study "Proteomic signatures improve risk predictions for common and rare diseases" (DOI pending) The provided scripts are not designed to work out of the box, but rather illustrate the main steps done for each of the analysis performed.

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑‍🔬

Code for aging project

LLM-based ontological extraction tools, including SPIRES

Phenome Health Utilities

A collection of utility functions and common tools used across Phenome Health projects and datasets. This package provides standardized methods for data processing, analysis, and visualization.