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.

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

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.)

CREDit (2020)

Chronological REference Datasets and Sites (CREDit) towards improved accuracy and precision in luminescence-based chronologies

Read More  

DEF2DEV (2019)

Identification of the mode of action of plant defensins during root development and plant defense responses.

Read More  

EngPTC2 (2019)

Exploring new technologies for the next generation pulse tube cryocooler below 2K

Read More