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ERMADA SIGNED

Illuminating Earth’s microbial diversity and origins from metagenomes with deep learning

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 ERMADA project word cloud

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

12       deep    deeper    community    uncharacterized    trained    origins    microbiome    nutrient    outnumbers    functions    stars    unknown    conventional    pertaining    bioinformatics    record    latter    serve    effort    plants    rank    levels    footprint    network    algorithms    machine    play    shotgun    milky    composition    cycles    metagenomic    microorganisms    patterns    volumes    environmental    dataset    elucidate    samples    prevalent    evolution    animals    biomass    exceeds    learning    networks    biogeochemical    circulation    analyze       classify    complete    terrestrial    regulating    gain    terabytes    biodiversity    sequence    data    capture    microbes    big    10    capacities    abstract    staggering    hundreds    twofold    emerged    structure    edge    painstaking    lineages    diversity    microbial    climate    taxonomically    whereas    cutting    species    cultured    classified    99    represented    similarity    genome    planet    neural    roles    habitats    employ    uncover    galaxy    earth    enzymes    marine    sequencing    sequences    models    genes    reference    environments    metabolic    classifying    govern   

Project "ERMADA" data sheet

The following table provides information about the project.

Coordinator
BIOMEDICAL SCIENCES RESEARCH CENTER ALEXANDER FLEMING 

Organization address
address: FLEMING STREET 34
city: VARI-ATHENS
postcode: 16672
website: www.fleming.gr

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 Greece [EL]
 Total cost 247˙628 €
 EC max contribution 247˙628 € (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-CAR
 Starting year 2019
 Duration (year-month-day) from 2019-08-01   to  2023-03-09

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    BIOMEDICAL SCIENCES RESEARCH CENTER ALEXANDER FLEMING EL (VARI-ATHENS) coordinator 247˙628.00

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 Project objective

The estimated number of microbes on our planet outnumbers the stars of the Milky Way galaxy and their biomass exceeds that of all plants and animals. Out of the 10^12 microbial species, only around 10^4 have been cultured, less than 10^5 species are represented by classified sequences, and a staggering estimated 99% of these microorganisms remain taxonomically unknown. Metagenomic shotgun sequencing has emerged as the most prevalent way of studying and classifying microorganisms from various habitats whereas genome analysis can be used to uncover the functions of genes, enzymes and metabolic pathways in a microbial community. This painstaking effort is crucial to understanding Earth's biodiversity, as microbes play important roles in regulating the planet’s biogeochemical cycles through processes that govern nutrient circulation in both terrestrial and marine environments. In this proposal, we will employ cutting edge bioinformatics and machine learning algorithms to analyze and elucidate Earth’s microbial diversity. We will use deep neural networks trained by large volumes of metagenomic sequences as well as big data methods to process hundreds of terabytes of data and taxonomically classify all uncharacterized metagenomic samples, by identifying their origins and habitats. Going beyond the capacities of conventional sequence similarity and comparison analyses, neural network models can capture higher level, abstract defining features and patterns in metagenomic sequences. The aim of this study is twofold: i) to gain a deeper understanding of the composition and structure of the microbiome at different rank levels and lineages and ii) to provide a complete record of the planet’s present microbial diversity footprint. The latter can serve as a reference dataset for future studies pertaining to microbiome evolution due to climate change or other long-term environmental factors.

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

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