MIMOmics

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Methods for Integrated analysis of Multiple Omics datasets
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A collaborative project funded by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 305280, research area FP7-HEALTH-2012-INNOVATION-1, topic HEALTH.2012.2.1.1-3: Statistical methods for collection and analysis of –omics data.
MIMOmics aims at developing robust and efficient statistical methods for the integrated analysis of metabolomics, glycomics, proteomic and genomic datasets in large studies.

It was triggered by the repeated observation that the existing methodology for analyzing huge data sets does not match by far the complexity of the biological problem addressed. Expensive and complex data are gathered and being analysed in a rather simple way, thereby missing the opportunity to uncover combinations of predictive and meaningful profiles among the different kinds of omics data. Novel methods should integrate multilevel omics data to bring biological understanding to the next level. Due to the high dimensionality of the datasets the multiple testing burden becomes heavier and consequently the false positive and negative rates increase. Super-meta methods combining multilevel data across populations need to be developed.

Due to the high dimensionality of the datasets the multiple testing burden becomes heavier and consequently the false positive and negative rates increase. Super-meta methods combining multilevel data across populations need to be developed.

GeneXPlain will provide the consortium with the geneXplain platform for data handling and analysis in order to integrate databases of molecular networks with state of the art bioinformatics and systems biology tools. This way, we will support the analysis of pre-existing omics data and apply them for building efficient systems biology models. We will also work on integrating analytical tools developed within the MIMOmics project with already existing systems biology data and knowledge. GeneXplain will be strongly involved in the project’s dissemination activities, thereby particularly considering potential partners from industries.

Publications

Stegmaier, P., Kel, A and Wingender, E. (2017) geneXplainR: An R interface for the geneXplain platform. J. Open Source Softw. 2, 412. doi: 10.21105/joss.00412. Link

Triska, M., Solovyev, V., Baranova, A., Kel, A. and Tatarinova, T. V. (2017) Nucleotide patterns aiding in prediction of eukaryotic promoters. PLoS One 12, e0187243. doi: 10.1371/journal.pone.0187243. Link

Kel, A.E. (2017). Search for Master Regulators in Walking Cancer Pathways. Methods Mol. Biol. 1613, 161-191. doi: 10.1007/978-1-4939-7027-8_8. Link

 

Further information

Homepage of MIMOmics.

Project description on the CORDIS server of the European Commission

Contract no.

305280.

Contract period

October 1st, 2012 – September 30th, 2017

Coordinator

The project is coordinated by Prof. Dr. Jeanine Houwing-Duistermaat,

Leiden University Medical Center, Leiden, The Netherlands.

The 14 participants of the consortium are from 7 European countries and Israel.

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