Single-cell multi-omics integration using Optimal Transport

A python framework for microbial natural products data mining by integrating genomics and metabolomics data

MOGONET (Multi-Omics Graph cOnvolutional NETworks) is multi-omics data integrative analysis framework for classification tasks in biomedical applications.

PathIntegrate Python package for pathway-based multi-omics data integration

COSMOS is a computational tool crafted to overcome the challenges associated with integrating spatially resolved multi-omics data. This software harnesses a graph neural network algorithm to deliver cutting-edge solutions for analyzing biological data that encompasses various omics types within a spatial framework.

NetICS: network-based integration of multi-omics data for prioritizing cancer genes

Code repository for "MyeVAE: A multi-omics variational autoencoder for predicting mortality in newly diagnosed myeloma patients"

Personal portfolio enumerating my main omic analyses projects

Complete scripts used to produce the results of Imperial MRes Biomedical Research - Data Science 2024-2025 Project 1.

COMPARISON OF MULTI-OMICS INTEGRATION METHODS

Joint analysis single-cell and spatial transcriptomics data with stSCI

Multi-omics integration for the classification of functional high risk patients in multiple myeloma.

ML based AI tool for personalised medicine utilising multi-omics data

A multiomics variational autoencoder for risk prediction in newly diagnosed multiple myeloma

Reproducibility repo for Shashikadze et al. "Multi-omics profiling of lungs from genetically diabetic pigs reveals reduced ALOX15 levels and impaired eicosanoid switching as mechanisms contributing to a proinflammatory milieu".