Opendata, web and dolomites

MARKTHEPIG SIGNED

Applied phenomics to identify biomarkers in pigs for new concepts in precision livestock farming

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 MARKTHEPIG project word cloud

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

metabolomics    full    changing    organisms    regions    datasets    university    insights    question    cell    health    pigs    tackle    environments    animal    spectrometry    influencing    characterising    translate    culture    productions    phenotypic    genome    omics    genetic    indirect    gene    technologies    advantage    tools    collections    sciences    variability    laboratory    genetics    time    phenotyped    traits    influence    understand    single    biologically    science    biological    density    precision    phenotyping    genomes    extensively    solving    sequencing    concert    dna    human    phenotype    ultimate    environment    populations    environmental    integration    bologna    diversity    questions    welfare    biomedical    phenotypes    proteomics    employed    patterns    instructions    phenomics    monitoring    populated    structure    livestock    farming    predict    accurately    interact    model    mass    individuals    made    spectrum    benefit    progress    considerable    spawned    organism    pig   

Project "MARKTHEPIG" data sheet

The following table provides information about the project.

Coordinator
ALMA MATER STUDIORUM - UNIVERSITA DI BOLOGNA 

Organization address
address: VIA ZAMBONI 33
city: BOLOGNA
postcode: 40126
website: www.unibo.it

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 Italy [IT]
 Project website http://markthepig.eu/
 Total cost 168˙277 €
 EC max contribution 168˙277 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2015
 Funding Scheme MSCA-IF-EF-CAR
 Starting year 2016
 Duration (year-month-day) from 2016-06-01   to  2018-05-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    ALMA MATER STUDIORUM - UNIVERSITA DI BOLOGNA IT (BOLOGNA) coordinator 168˙277.00

Map

 Project objective

Considerable progress has been made in characterising genomes, allowing comprehensive insights into patterns of genetic diversity in many organisms. However, the question of how genetics and environment interact to influence phenotype still remains challenging. Recent advances in DNA sequencing and phenotyping technologies, in concert with analysis of large datasets have spawned 'phenomics', the use of large scale approaches to study how genetic instructions from a single gene or the whole genome translate into the full set of phenotypic traits of an organism. Phenomics can be used across the full range of biological sciences, from cell culture studies in well-defined laboratory environments to populations of organisms under rapidly changing conditions. Advances in “omics” technologies, are providing the necessary tools to extensively phenotype increasingly large collections of individuals. The application and integration of these technologies in animal science will provide great opportunities to tackle biologically important questions (e.g. how to improve animal welfare, the environmental impact) at a whole new level. Indeed, these information could be used to develop precision livestock farming with the ultimate aim to offer a real-time monitoring and management system, solving in part problems of animal productions in high density populated regions, like Europe.

The aim of the current project is to take advantage of the knowledge obtained by the University of Bologna in highly phenotyped pigs to better understand the factors, both genetic and non-genetic, that contribute to its variability. In the project, the use of mass spectrometry-based proteomics and metabolomics, will be the approach employed to provide new insights into the spectrum and structure of phenotypic diversity and the characteristics influencing the ability to accurately predict phenotypes.

Indirect benefit for human health will be obtained by strengthening the pig as a biomedical model.

 Publications

year authors and title journal last update
List of publications.
2018 Samuele Bovo, Alessio Di Luca, Giuliano Galimberti, Stefania Dall’Olio, Luca Fontanesi
A comparative analysis of label-free liquid chromatography-mass spectrometry liver proteomic profiles highlights metabolic differences between pig breeds
published pages: e0199649, ISSN: 1932-6203, DOI: 10.1371/journal.pone.0199649
PLOS ONE 13/9 2019-06-13
2018 Samuele Bovo1, Alessio Di Luca1, Giuliano Galimberti, Stefania Dall\'Olio, Luca Fontanesi 1These Authors contributed equally to this work
A comparative analysis of label-free liquid chromatography-mass spectrometry liver proteomic profiles highlights metabolic differences between pig breeds
published pages: , ISSN: , DOI: 10.1101/346056
bioRxiv 2019-06-13

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "MARKTHEPIG" 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 "MARKTHEPIG" are provided by the European Opendata Portal: CORDIS opendata.

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

Comedy and Politics (2018)

The Comedy of Political Philosophy. Democratic Citizenship, Political Judgment, and Ideals in Political Practice.

Read More  

DIFFER (2020)

Determinants of genetic diversity: Important Factors For Ecosystem Resilience

Read More  

SingleCellAI (2019)

Deep-learning models of CRISPR-engineered cells define a rulebook of cellular transdifferentiation

Read More