Evidence map›Paper›PMID 32838759›Full record

ArticleBMC bioinformatics2020

ELIXIR-IT HPC@CINECA: high performance computing resources for the bioinformatics community.

Tiziana Castrignanò, Silvia Gioiosa, Tiziano Flati, Mirko Cestari, Ernesto Picardi, Matteo Chiara, Maddalena Fratelli, Stefano Amente, Marco Cirilli, Marco Antonio Tangaro and 3 more

Abstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed.

  1. Article
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  6. MultipleFood and waterborne parasitology · 2025
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  8. Molecular Dynamics Simulations of the SPRED2International journal of molecular sciences · 2025
    Article
  9. Article
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  11. Article
  12. Article
  13. Transcriptomic profile of the zoonotic parasiteFrontiers in cellular and infection microbiology · 2025
    Article
  14. Article
  15. Article
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  17. Article
  18. High clonality ofFrontiers in veterinary science · 2024
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Tiziana CastrignanòDepartment of Ecological and Biological Sciences (DEB), University of Tuscia, Viterbo, Italy. tiziana.castrignano@unitus.it.
Silvia GioiosaCINECA, SuperComputing Applications and Innovation Department, Rome, Italy.
Tiziano FlatiCINECA, SuperComputing Applications and Innovation Department, Rome, Italy.
Mirko CestariCINECA, SuperComputing Applications and Innovation Department, Rome, Italy.
Ernesto PicardiInstitute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (IBIOM-CNR), Bari, Italy.
Matteo ChiaraInstitute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (IBIOM-CNR), Bari, Italy.
Maddalena FratelliIRCCS-Istituto di Ricerche Farmacologiche "Mario Negri", Milano, Milan, Italy.
Stefano AmenteDepartment of Molecular Medicine and Medical Biotechnologies, University of Naples 'Federico II', Naples, Italy.
Marco CirilliDepartment of Agricultural and Environmental Sciences - Production, Landscape, Agroenergy (DISAA), University of Milan, Milan, Italy.
Marco Antonio TangaroInstitute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (IBIOM-CNR), Bari, Italy.
Giovanni ChillemiInstitute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (IBIOM-CNR), Bari, Italy.
Graziano PesoleInstitute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (IBIOM-CNR), Bari, Italy. graziano.pesole@uniba.it.
Federico ZambelliInstitute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (IBIOM-CNR), Bari, Italy. federico.zambelli@unimi.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe advent of Next Generation Sequencing (NGS) technologies and the concomitant reduction in sequencing costs allows unprecedented high throughput profiling of biological systems in a cost-efficient manner. Modern biological experiments are increasingly becoming both data and computationally intensive and the wealth of publicly available biological data is introducing bioinformatics into the "Big Data" era. For these reasons, the effective application of High Performance Computing (HPC) architectures is becoming progressively more recognized also by bioinformaticians. Here we describe HPC resources provisioning pilot programs dedicated to bioinformaticians, run by the Italian Node of ELIXIR (ELIXIR-IT) in collaboration with CINECA, the main Italian supercomputing center.

resultsStarting from April 2016, CINECA and ELIXIR-IT launched the pilot Call "ELIXIR-IT HPC@CINECA", offering streamlined access to HPC resources for bioinformatics. Resources are made available either through web front-ends to dedicated workflows developed at CINECA or by providing direct access to the High Performance Computing systems through a standard command-line interface tailored for bioinformatics data analysis. This allows to offer to the biomedical research community a production scale environment, continuously updated with the latest available versions of publicly available reference datasets and bioinformatic tools. Currently, 63 research projects have gained access to the HPC@CINECA program, for a total handout of ~ 8 Millions of CPU/hours and, for data storage, ~ 100 TB of permanent and ~ 300 TB of temporary space.

conclusionsThree years after the beginning of the ELIXIR-IT HPC@CINECA program, we can appreciate its impact over the Italian bioinformatics community and draw some considerations. Several Italian researchers who applied to the program have gained access to one of the top-ranking public scientific supercomputing facilities in Europe. Those investigators had the opportunity to sensibly reduce computational turnaround times in their research projects and to process massive amounts of data, pursuing research approaches that would have been otherwise difficult or impossible to undertake. Moreover, by taking advantage of the wealth of documentation and training material provided by CINECA, participants had the opportunity to improve their skills in the usage of HPC systems and be better positioned to apply to similar EU programs of greater scale, such as PRACE. To illustrate the effective usage and impact of the resources awarded by the program - in different research applications - we report five successful use cases, which have already published their findings in peer-reviewed journals.

Indexed as

Computational BiologyComputing MethodologiesSoftwareAlgorithmsAnimalsCell LineDatabases, GeneticGene FusionGenomeHumansPrunus persicaRNA EditingSwallowsBioinformaticsCompute serviceHPCNGS data analysisSoftware environment

Identifiers

PMID32838759
PMCPMC7446135

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.