Single-cell multi-omics integration using Optimal Transport
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Updated
Aug 14, 2025 - Python
Single-cell multi-omics integration using Optimal Transport
A python framework for microbial natural products data mining by integrating genomics and metabolomics data
PathIntegrate Python package for pathway-based multi-omics data integration
MOGONET (Multi-Omics Graph cOnvolutional NETworks) is multi-omics data integrative analysis framework for classification tasks in biomedical applications.
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.
Multimodal Integration with Modality-agnostic Autoencoders - Developed by LMIB @ KU Leuven
SMART is a computational framework for spatial multi-omic integration. SMART leverages a modality-independent modular and stacking framework with spatial coordinates and adjusts the aggregation using triplet relationships.
Joint analysis single-cell and spatial transcriptomics data with stSCI
Curated and evolving portfolio of my computational genomics and bioinformatics projects, including data modeling, phylogenetic profiling, and multi-omics integration.
End-to-end computational platform for pharmaceutical-grade cancer biomarker discovery. Integrates multi-omics data, machine learning, and clinical validation frameworks for precision oncology applications.
Geospatial Factors Shape the Human Brain-Gut-Microbiome System Minimal Reproducible Analysis: This repository ships a compact, execution‑ready subset of code to reproduce the manuscript’s core statistical findings: dose–response screens, cross‑modal integration (sPLS‑DA/DIABLO), and a publication‑style volcano plot.
Code repository for "MyeVAE: A multi-omics variational autoencoder for predicting mortality in newly diagnosed myeloma patients"
NetICS: network-based integration of multi-omics data for prioritizing cancer genes
A multiomics variational autoencoder for risk prediction in newly diagnosed multiple myeloma
Project from workshop "Introduction to multi-omics data integration and visualisation" @embl-ebi
2022-2023: A multi-omics biomedical text-mining pipeline for extracting protein-disease associations + a knowledge graph prediciton pipeline to predict protein-disease associations. Leverages biological knowledge bases, PubMed, and biomedical ontologies
Personal portfolio enumerating my main omic analyses projects
Interpretable multimodal neural network framework that integrates single-cell and spatial omics through biologically constrained, concept-bottleneck architectures.
Integration of metagenomics and metabolomics data to explore the dynamics during the alcoholic fermentation process
Complete scripts used to produce the results of Imperial MRes Biomedical Research - Data Science 2024-2025 Project 1.
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