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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.

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

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

Map

 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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