Evidence map›Paper›PMID 40662129›Full record

ArticleFrontiers in bioinformatics2025

Long-read microbial genome assembly, gene prediction and functional annotation: a service of the MIRRI ERIC Italian node.

Sandro Gepiro Contaldo, Antonio d'Acierno, Lorenzo Bosio, Francesco Venice, Elisa Li Perottino, Janneth Estefania Hoyos Rea, Giovanna Cristina Varese, Francesca Cordero, Marco Beccuti

Abstract read
In one paragraph

Article in Frontiers in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Sandro Gepiro ContaldoDepartment of Computer Science, University of Torino, Turin, Italy.
Antonio d'AciernoInstitute of Food Sciences, Consiglio Nazionale delle Ricerche-Istituto di Scienze dell'alimentazione, Avellino, Italy.
Lorenzo BosioDepartment of Computer Science, University of Torino, Turin, Italy.
Francesco VeniceDepartment of Life Sciences and Systems Biology, Mycotheca Universitatis Taurinensis, University of Torino, Turin, Italy.
Elisa Li PerottinoDepartment of Computer Science, University of Torino, Turin, Italy.
Janneth Estefania Hoyos ReaDepartment of Computer Science, University of Torino, Turin, Italy.
Giovanna Cristina VareseDepartment of Life Sciences and Systems Biology, Mycotheca Universitatis Taurinensis, University of Torino, Turin, Italy.
Francesca CorderoDepartment of Computer Science, University of Torino, Turin, Italy.
Marco BeccutiDepartment of Computer Science, University of Torino, Turin, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Understanding the structure and function of microbial genomes is crucial for uncovering their ecological roles, evolutionary trajectories, and potential applications in health, biotechnology, agriculture, food production, and environmental science. However, genome reconstruction and annotation remain computationally demanding and technically complex. Results: We introduce a bioinformatics platform designed explicitly for long-read microbial sequencing data to address these challenges. Developed as a service of the Italian MIRRI ERIC node, the platform provides a comprehensive solution for analyzing both prokaryotic and eukaryotic genomes, from assembly to functional protein annotation. It integrates state-of-the-art tools (e.g., Canu, Flye, BRAKER3, Prokka, InterProScan) within a reproducible, scalable workflow built on the Common Workflow Language and accelerated through high-performance computing infrastructure. A user-friendly web interface ensures accessibility, even for non-specialists. Conclusion: Through case studies involving three environmentally and clinically significant microorganisms, we demonstrate the ability of the platform to produce reliable, biologically meaningful insights, positioning it as a valuable tool for routine genome analysis and advanced microbial research.

Indexed as

functional annotationgene predictiongenome assemblyHPC and cloud servicereproducible analysis

Identifiers

PMID40662129
PMCPMC12256462

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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.