Opendata, web and dolomites

Visual Proteomics SIGNED

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

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 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.

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

Project "Visual Proteomics" data sheet

The following table provides information about the project.

Coordinator
KOBENHAVNS UNIVERSITET 

Organization address
address: NORREGADE 10
city: KOBENHAVN
postcode: 1165
website: www.ku.dk

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

 Partnership

Take a look of project's partnership.

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

Map

 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.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "VISUAL PROTEOMICS" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

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

More projects from the same programme (H2020-EU.1.3.2.)

LiverMacRegenCircuit (2020)

Elucidating the role of macrophages in liver regeneration and tissue unit formation

Read More  

MY MITOCOMPLEX (2021)

Functional relevance of mitochondrial supercomplex assembly in myeloid cells

Read More  

NarrowbandSSL (2019)

Development of Narrow Band Blue and Red Emitting Macromolecules for Solution-Processed Solid State Lighting Devices

Read More