Project: Multi-omics data integration to elucidate the causes of complex diseases
2020-03-01 – 2026-02-28
- Abstract
Recent technological advances enable cost-efficient, high-throughput analysis of multiple biologic molecules and molecular interactions, which lead to a wealth of omics data: genome, epigenome, transcriptome, proteome, metabolome, ... The capacity to integrate multi-omics data, to something more than the sum of the existing data, is key to elucidating the causes of complex diseases such as neuro-inflammatory disorders and cancer. Multi-omics data integration is still in its infancy and many tools are tailored towards specific applications, data types or gene sets. In this project we will compare, optimize, develop and subsequently apply methods for multi-omics data integration. Special attention will be given to the impact of the environment such as microbiota and diet on regulatory networks of complex diseases through the integration of transcriptomics, epigenomics and metabolomics.
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- Journal Article
- A1
- open access
A single-cell multimodal view on gene regulatory network inference from transcriptomics and chromatin accessibility data
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- Journal Article
- A1
- open access
Evaluation of single-sample network inference methods for precision oncology
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- Journal Article
- A1
- open access
Molecular systems biology approaches to investigate mechanisms of gut-brain communication in neurological diseases
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- Journal Article
- A1
- open access
SUBATOMIC : a SUbgraph BAsed mulTi-OMIcs clustering framework to analyze integrated multi-edge networks