Prediction, prioritization and validation of body fluid biomarkers for cancer and cardiovascular diseases

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Research unit

INNOSUISSE

Project number

12396.1;13 PFLS-LS

Project title

Prediction, prioritization and validation of body fluid biomarkers for cancer and cardiovascular diseases

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Short description	-	-	-
Abstract	-	-	-

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Short description (English)	Prediction, prioritization and validation of body fluid biomarkers for cancer and cardiovascular diseases
Abstract (English)	In this follow-up project, we will generate immediate and high commercial value from the previous KTI project by discovering, prioritizing, and validating potential mRNA and protein biomarkers for applications on body fluids. In a first step, we will adjust our existing data mining engine to optimally integrate the biomarker prediction workflow for this project. This will be achieved together with a network of project partners from ETH, USZ, and several start-up companies. In a second step, we will use this pipeline for biomarker discovery in cardiovascular diseases (together with USZ) and cancer (together with ETH, ProteoMediX, Diagnoplex and Biognosys). We show in Appendix II and III several proofs of principle for various scenarios using our existing tools.

Category

Text

Short description
(English)

Prediction, prioritization and validation of body fluid biomarkers for cancer and cardiovascular diseases

Abstract
(English)

In this follow-up project, we will generate immediate and high commercial value from the previous KTI project by discovering, prioritizing, and validating potential mRNA and protein biomarkers for applications on body fluids. In a first step, we will adjust our existing data mining engine to optimally integrate the biomarker prediction workflow for this project. This will be achieved together with a network of project partners from ETH, USZ, and several start-up companies. In a second step, we will use this pipeline for biomarker discovery in cardiovascular diseases (together with USZ) and cancer (together with ETH, ProteoMediX, Diagnoplex and Biognosys). We show in Appendix II and III several proofs of principle for various scenarios using our existing tools.