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Integration of single-cell multi-omics data across space and time to unlock cellular trajectories

MULTIview-CELL aims to integrate multi-omics single-cell data using novel MML approaches to uncover spatiotemporal cell trajectories and molecular regulators, enhancing biological understanding and health outcomes.

Subsidie
€ 1.285.938
2024

Projectdetails

Introduction

The introduction of high-throughput single-cell sequencing has produced a flood of data at the resolution of the single cell, including spatiotemporal information and different molecular facets of a cell, a.k.a. multi-omics. Their integration through MultiModal Learning (MML), aimed at combining multiple complementary views, offers great promise to understand the spatiotemporal phenotypic evolution of a cell and its molecular regulators.

Computational Challenges

However, integrating multi-omics data across space and time is a huge computational challenge requiring radically new MML approaches.

Project Overview

MULTIview-CELL will infer multimodal spatiotemporal phenotypic cell trajectories by:

  1. Combining back-translation to allow the unsupervised dimensionality reduction of multimodal data.
  2. Utilizing a new Optimal Transport distance, allowing the spatiotemporal pairing of cells (Aim 1).

MULTIview-CELL will then pinpoint the molecular regulators of such trajectories by:

  1. Combining new Graph Convolutional Networks with topological evolutions.
  2. Utilizing Heterogeneous Multilayer Graphs, allowing the integration of graphs inferred from multimodal data (Aim 2).

Finally, all developed methods will be implemented in open-source software, with an emphasis on GPU-friendly scalable computations, a unique feature among existing single-cell tools (Aim 3).

Impact on Machine Learning and Biology

These core contributions will impact Machine Learning, but more importantly, will have profound biological implications.

Applications and Validation

The application of the tools developed to cutting-edge single-cell data from muscle stem cells will lead to new biological hypotheses on their heterogeneity and crosstalk, to be validated through wet-lab experiments (Transversal Tasks).

Long-term Goals

In addition, by allowing to answer longstanding questions on the spatiotemporal phenotypic evolution of a cell, MULTIview-CELL will catalyze the generation of crucial knowledge in fundamental biology. It will be key to preventing disease onset or therapy resistance, thus impacting health, society, and economy.

Financiële details & Tijdlijn

Financiële details

Subsidiebedrag€ 1.285.938
Totale projectbegroting€ 1.285.938

Tijdlijn

Startdatum1-4-2024
Einddatum31-3-2029
Subsidiejaar2024

Partners & Locaties

Projectpartners

  • CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRSpenvoerder

Land(en)

France

Inhoudsopgave

European Research Council

Financiering tot €10 miljoen voor baanbrekend frontier-onderzoek via ERC-grants (Starting, Consolidator, Advanced, Synergy, Proof of Concept).

Bekijk regeling

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