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Visual Proteomics SIGNED

Biomarker discovery by AI-guided, image based single-cell isolation proteomics

Total Cost €


EC-Contrib. €






 Visual Proteomics project word cloud

Explore the words cloud of the Visual Proteomics project. It provides you a very rough idea of what is the project "Visual Proteomics" about.

machine    artificial    receive    perform    niche    microscopic    ground    disease    automated    candidates    techniques    molecular    resolution    image    samples    expression    expertise    critically    proteins    microdissection    malignancies    discoveries    morphology    attempt    pipeline    laboratory    career    survival    cell    followed    array    severe    profiling    protein    clinical    inspire    archival    class    pathology    identity    outside    collaborative    personalized    tissues    patient    form    cells    proteome    shown    prospective    complement    map    impede    exploits    limited    laser    treatment    ubiquitous    unresolved    workflow    correlate    training    averaged    diagnosis    populations    microscopy    therapies    biomarkers    unprecedented    competitive    proteomics    learning    edge    composition    sensitivity    stimulate    solid    me    outcome    detection    tumor    early    fertile    world    cutting    ffpe    acquisition    guided    individual    critical    biobank    intelligence    biomarker    individually    isolated    tissue    cellular    prediction    cancer    optimize    diseases    host    descriptions    heterogeneity    retrospective   

Project "Visual Proteomics" data sheet

The following table provides information about the project.


Organization address
address: NORREGADE 10
postcode: 1165

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Denmark [DK]
 Total cost 207˙312 €
 EC max contribution 207˙312 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2018
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2019
 Duration (year-month-day) from 2019-04-01   to  2021-03-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    KOBENHAVNS UNIVERSITET DK (KOBENHAVN) coordinator 207˙312.00


 Project objective

Early detection of severe malignancies such as cancer is the most effective way to increase patient survival, but early diagnosis and prediction of treatment outcome critically depend on disease-specific biomarkers. However, molecular and cellular disease heterogeneity provide a ubiquitous and unresolved challenge to this important task, and therefore impede any attempt to develop personalized therapies. Past and current approaches provide “averaged” descriptions of the tumor composition and have shown very limited success to identify biomarkers. This is likely due to the failure of these methods to identify the critical disease promoting cell populations within the tumor. Therefore, I will develop a new workflow that exploits automated microscopic image acquisition and artificial-intelligence-guided image analysis to identify specific cell populations in patient samples. These cells are then individually isolated by laser microdissection, followed by high-sensitivity proteome profiling, to identify proteins that define the identity of individual cells in a given tumor and thus represent the most promising biomarker candidates. To apply my approach to wide array of diseases, I will optimize it for archival biobank tissues (FFPE), the most common form of solid tissues in pathology. Applied to FFPE samples, my approach will allow me to perform both prospective and retrospective studies, correlate disease state and tissue morphology to protein expression and clinical outcome, and map tumor heterogeneity with unprecedented resolution. To achieve this, I will receive world-class training in cutting-edge microscopy and machine learning techniques in my host laboratory, which I complement with my expertise in high-sensitivity proteomics. My new pipeline will offer a highly fertile ground for new biomarker discoveries, inspire and stimulate collaborative research within and outside the host institute and allow me to establish a highly competitive niche for my future career.

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The information about "VISUAL PROTEOMICS" are provided by the European Opendata Portal: CORDIS opendata.

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