Explore the words cloud of the GeCo project. It provides you a very rough idea of what is the project "GeCo" about.
The following table provides information about the project.
Coordinator |
POLITECNICO DI MILANO
Organization address contact info |
Coordinator Country | Italy [IT] |
Project website | http://www.bioinformatics.deib.polimi.it/geco/ |
Total cost | 2˙500˙000 € |
EC max contribution | 2˙500˙000 € (100%) |
Programme |
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC)) |
Code Call | ERC-2015-AdG |
Funding Scheme | ERC-ADG |
Starting year | 2016 |
Duration (year-month-day) | from 2016-09-01 to 2021-08-31 |
Take a look of project's partnership.
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1 | POLITECNICO DI MILANO | IT (MILANO) | coordinator | 2˙500˙000.00 |
Next-generation sequencing technology has dramatically reduced the cost and time of reading the DNA. Huge investments are targeted to sequencing the DNA of large populations, and repositories of well-curated sequence data are being collected. Answers to fundamental biomedical problems are hidden in these data, e.g. how cancer arises, how driving mutations occur, how much cancer is dependent on environment. But genomic computing has not comparatively evolved. Bioinformatics has been driven by specific needs and distracted from a foundational approach; hundreds of methods solve individual problems, but miss the broad perspective.
The objective of GeCo is to rethink genomic computing through the lens of basic data management. We will first design the data model, using few general abstractions that guarantee interoperability between existing data formats. Next, we will design a new-generation query language inspired by classic relational algebra and extended with orthogonal, domain-specific abstractions for genomics. Query processing will trace metadata and computation steps, opening doors to the seamless integration of descriptive statistics and high-level data analysis (e.g., DNA region clustering and extraction of regulatory networks).
Genomic computing is a “big data” problem, therefore we will also achieve computational efficiency by using parallel computing on both clusters and public clouds; the choice of a suitable data model and of computational abstractions will boost performance in a principled way. The resulting technology will be applicable to individual and federated repositories, and will be exploited for providing integrated access to curated data, made available by large consortia, through user-friendly search services. Our most far-fetching vision is to move towards an Internet of Genomes exploiting data indexing and crawling. The PI’s background in distributed data, data modelling, query processing and search will drive a radical paradigm shift.
year | authors and title | journal | last update |
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2018 |
Marco Masseroli, Arif Canakoglu, Pietro Pinoli, Abdulrahman Kaitoua, Andrea Gulino, Olha Horlova, Luca Nanni, Anna Bernasconi, Stefano Perna, Eirini Stamoulakatou, Stefano Ceri Processing of big heterogeneous genomic datasets for tertiary analysis of Next Generation Sequencing data published pages: , ISSN: 1367-4803, DOI: 10.1093/bioinformatics/bty688 |
Bioinformatics | 2019-06-14 |
2017 |
Fabio Cumbo, Giulia Fiscon, Stefano Ceri, Marco Masseroli, Emanuel Weitschek TCGA2BED: extracting, extending, integrating, and querying The Cancer Genome Atlas published pages: , ISSN: 1471-2105, DOI: 10.1186/s12859-016-1419-5 |
BMC Bioinformatics 18/1 | 2019-06-14 |
2017 |
Vahid Jalili, Matteo Matteucci, Marco Masseroli, Stefano Ceri Explorative visual analytics on interval-based genomic data and their metadata published pages: , ISSN: 1471-2105, DOI: 10.1186/s12859-017-1945-9 |
BMC Bioinformatics 18/1 | 2019-06-14 |
2017 |
Abdulrahman Kaitoua, Pietro Pinoli, Michele Bertoni, Stefano Ceri Framework for Supporting Genomic Operations published pages: 443-457, ISSN: 0018-9340, DOI: 10.1109/TC.2016.2603980 |
IEEE Transactions on Computers 66/3 | 2019-06-14 |
2018 |
Fabrizio Celli, Fabio Cumbo, Emanuel Weitschek Classification of Large DNA Methylation Datasets for Identifying Cancer Drivers published pages: , ISSN: 2214-5796, DOI: 10.1016/j.bdr.2018.02.005 |
Big Data Research | 2019-06-14 |
2017 |
Alice Cambiaghi, Manuela Ferrario, Marco Masseroli Analysis of metabolomic data: tools, current strategies and future challenges for omics data integration published pages: bbw031, ISSN: 1467-5463, DOI: 10.1093/bib/bbw031 |
Briefings in Bioinformatics | 2019-06-14 |
2017 |
Stefano Ceri, Abdulrahman Kaitoua, Marco Masseroli, Pietro Pinoli, Francesco Venco Data Management for Heterogeneous Genomic Datasets published pages: 1251-1264, ISSN: 1545-5963, DOI: 10.1109/TCBB.2016.2576447 |
IEEE/ACM Transactions on Computational Biology and Bioinformatics 14/6 | 2019-06-14 |
2017 |
Vahid Jalili, Matteo Matteucci, Marco Masseroli, Stefano Ceri Indexing Next-Generation Sequencing data published pages: 90-109, ISSN: 0020-0255, DOI: 10.1016/j.ins.2016.08.085 |
Information Sciences 384 | 2019-06-14 |
2017 |
Vahid Jalili, Matteo Matteucci, Marco J. Morelli, Marco Masseroli MuSERA: Multiple Sample Enriched Region Assessment published pages: bbw029, ISSN: 1467-5463, DOI: 10.1093/bib/bbw029 |
Briefings in Bioinformatics 18 (3) | 2019-06-14 |
2019 |
Pietro Pinoli, Stefano Ceri, Davide Martinenghi, Luca Nanni Metadata management for scientific databases published pages: 1-20, ISSN: 0306-4379, DOI: 10.1016/j.is.2018.10.002 |
Information Systems 81 | 2019-04-18 |
2018 |
Stefano Perna, Pietro Pinoli, Stefano Ceri, Limsoon Wong TICA: Transcriptional Interaction and Coregulation Analyzer published pages: 342-353, ISSN: 1672-0229, DOI: 10.1016/j.gpb.2018.05.004 |
Genomics, Proteomics & Bioinformatics 16/5 | 2019-04-18 |
2019 |
Andrea Gulino, Abdulrahman Kaitoua, Stefano Ceri Optimal Binning for Genomics published pages: 125-138, ISSN: 0018-9340, DOI: 10.1109/tc.2018.2854880 |
IEEE Transactions on Computers 68/1 | 2019-04-18 |
2019 |
Cheng Wang, Luca Nanni, Boris Novakovic, Wout Megchelenbrink, Tatyana Kuznetsova, Hendrik G. Stunnenberg, Stefano Ceri, Colin Logie Extensive epigenomic integration of the glucocorticoid response in primary human monocytes and in vitro derived macrophages published pages: , ISSN: 2045-2322, DOI: 10.1038/s41598-019-39395-9 |
Scientific Reports 9/1 | 2019-04-18 |
2018 |
Vahid Jalili, Matteo Matteucci, Jeremy Goecks, Yashar Deldjoo, Stefano Ceri Next Generation Indexing for Genomic Intervals published pages: 1-1, ISSN: 1041-4347, DOI: 10.1109/tkde.2018.2871031 |
IEEE Transactions on Knowledge and Data Engineering | 2019-04-18 |
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