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MRG-GRammar

Massive Reverse Genomics to Decipher Gene Regulatory Grammar

Total Cost €

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EC-Contrib. €

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Partnership

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 MRG-GRammar project word cloud

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

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Project "MRG-GRammar" data sheet

The following table provides information about the project.

Coordinator
TECHNION - ISRAEL INSTITUTE OF TECHNOLOGY 

Organization address
address: SENATE BUILDING TECHNION CITY
city: HAIFA
postcode: 32000
website: www.technion.ac.il

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 Israel [IL]
 Project website http://www.mrg-grammar.eu
 Total cost 3˙999˙661 €
 EC max contribution 3˙999˙661 € (100%)
 Programme 1. H2020-EU.1.2.1. (FET Open)
 Code Call H2020-FETOPEN-2014-2015-RIA
 Funding Scheme RIA
 Starting year 2015
 Duration (year-month-day) from 2015-08-01   to  2018-07-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    TECHNION - ISRAEL INSTITUTE OF TECHNOLOGY IL (HAIFA) coordinator 902˙000.00
2    EUROPEAN MOLECULAR BIOLOGY LABORATORY DE (HEIDELBERG) participant 850˙848.00
3    WEIZMANN INSTITUTE OF SCIENCE IL (REHOVOT) participant 721˙273.00
4    KAROLINSKA INSTITUTET SE (STOCKHOLM) participant 716˙138.00
5    GENOME RESEARCH LIMITED UK (LONDON) participant 581˙651.00
6    IMPASARA LIMITED UK (LONDON) participant 189˙000.00
7    AGILENT TECHNOLOGIES LDA ISRAEL LTD IL (PETACH TIKVA) participant 38˙750.00

Map

 Project objective

MRG-GRammar aims to devise an entirely new strategy for deciphering the regulatory rules of gene regulation. We will leverage Synthetic Biology with cutting-edge DNA synthesis technologies and high-throughput analysis to generate new types of biological datasets that systematically explore all possible regulatory landscapes rather than just the naturally occurring regulatory sequences. The extensive and unbiased nature of these unique datasets will allow us to build new models explaining different aspects of regulatory activity, which will be tested in second-generation libraries, designed based on model predictions. Consequently, through such an iterative process, we expect to make a significant breakthrough in deciphering, and evolving, the regulatory code. Our strategy synergizes four orthogonal objectives that will form a new knowledge base from which the regulatory algorithm can be derived. We will employ our strategy on diverse model organisms from the tree of life, from single cell to whole organism: bacteria, yeast, mouse ex-vivo cells, human cell-lines and finally, whole D. melanogaster and mouse embryos. We expect this multidisciplinary synthetic biology approach to generate a major technological advance, which will provide the community with algorithms that will not only decipher extant natural regulatory code, but also interpret variations leading to a profoundly deeper understanding of the origins of many diseases. We expect our models to also serve as a reference in designing and implementing accurate and more controllable synthetic biology devices, with applications in fuel production, healthcare and other industrial fields. Thus, our ultimate goal is to substantially accelerate the advance of technologies and knowledge related to generating systematic and personal therapeutic solutions based on the analysis of each individual's natural genomic variations.

 Deliverables

List of deliverables.
Website Other 2019-05-31 10:17:19

Take a look to the deliverables list in detail:  detailed list of MRG-GRammar deliverables.

 Publications

year authors and title journal last update
List of publications.
2018 Edward Vitkin, Oz Solomon, Sharon Sultan, Zohar Yakhini
Genome-wide analysis of fitness data and its application to improve metabolic models
published pages: , ISSN: 1471-2105, DOI: 10.1186/s12859-018-2341-9
BMC Bioinformatics 19/1 2019-05-29
2018 Eileen E. M. Furlong, Michael Levine
Developmental enhancers and chromosome topology
published pages: , ISSN: 1095-9203, DOI: 10.1126/science.aau0320
Science 2019-04-04
2017 Lior Levy, Leon Anavy, Oz Solomon, Roni Cohen, Michal Brunwasser-Meirom, Shilo Ohayon, Orna Atar, Sarah Goldberg, Zohar Yakhini, Roee Amit
A Synthetic Oligo Library and Sequencing Approach Reveals an Insulation Mechanism Encoded within Bacterial σ 54 Promoters
published pages: 845-858, ISSN: 2211-1247, DOI: 10.1016/j.celrep.2017.09.063
Cell Reports 21/3 2019-04-03

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The information about "MRG-GRAMMAR" are provided by the European Opendata Portal: CORDIS opendata.

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