Computational Biology and Bioinformatics
The Unit develops bioinformatics tools for pathogen characterisation and advanced machine learning models to predict pathogen phenotypes from genomic data. These resources are made available through the national bioinformatics platform of the National Reference Centre GENPAT, a key tool for genomic surveillance of pathogenic microorganisms within a One Health framework.
The Unit primarily develops open-source software components, which are shared with the scientific community.
The Unit’s team of experts ensures the production, maintenance and execution of bioinformatics analyses based on high-throughput sequencing data (NGS – Next Generation Sequencing), in support of the Institute’s scientific research and molecular diagnostics.
In this context, the team develops bioinformatics tools tailored to the needs of the Institute’s laboratories and centres of excellence. It also manages the bioinformatics platform of the National Reference Centre for the Genomic Sequences of Pathogenic Microorganisms, overseeing both the database and related analyses: https://genpat.izs.it.
The Unit is also involved in research and development in the field of computational bioinformatics, with a particular focus on the application of computational biology algorithms and machine learning techniques. These approaches are used to predict pathogen phenotypes based on genomic data, including:
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Source attribution of zoonotic and foodborne pathogens, using predictive models capable of identifying the likely origin of strains isolated in humans;
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Analysis and prediction of antimicrobial resistance (AMR) and disinfectant resistance, using algorithms that correlate genomic profiles with resistant phenotypes, supporting the monitoring and prevention of the spread of multidrug-resistant strains.
The software developed is released under open-source licences and made available to the scientific community through the Institute’s GitHub channel. Many of these solutions have been adopted by national and international institutions. These include:
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Versions of the GENPAT bioinformatics platform, currently in use or under development:
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COHESIVE: a public demo is available showcasing its main features.
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COHESIVE@INSA: in use at the Instituto Nacional de Saúde Doutor Ricardo Jorge (INSA), Portugal.
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MEDNET4OH: currently being developed for the Ministry of Health of Tunisia.
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GENPAT-VETLAB: developed at the request of the International Atomic Energy Agency (IAEA).
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- ReporTree: an advanced bioinformatics tool developed in collaboration with INSA to strengthen genomic surveillance of pathogens.
- SPREAD: an interactive dashboard offering spatial and temporal visualisation features integrated with genomic data generated by ReporTree. It is currently used by both INSA and the ARIES team (Advanced Research Infrastructure for Experimentation in GenomicS) at the Istituto Superiore di Sanità for cluster analysis.
- Wiki-engine: an automated documentation system used by EFSA for producing the manual for its One Health WGS system.
- + - Our Research
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- + - Head
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Adriano Di Pasquale
Head
Adriano Di Pasquale holds a PhD in Computer Science from the University of Rome “La Sapienza” and has lectured at the University of Rome “Tor Vergata”. He has been working at the Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise since 2002.
Adriano Di Pasquale holds a PhD in Computer Science from the University of Rome “La Sapienza” and has lectured at the University of Rome “Tor Vergata”. He has been working at the Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise since 2002.
His work has focused primarily on the analysis and development of veterinary information systems for the Italian Ministry of Health; on national and international research and cooperation projects as an IT expert; and on bioinformatics applied to microorganisms.
In 2016, he worked at the European Food Safety Authority (EFSA) as a Contract Agent – Data Manager.
Since 2018, he has led the Bioinformatics Unit at IZSAM and coordinates the development of the bioinformatics platform for the National Reference Centre GENPAT.
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- + - Selected papers
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SPREAD: Spatiotemporal Pathogen Relationships and Epidemiological Analysis Dashboard.
De Ruvo, A., De Luca, A., Bucciacchio, A., Castelli, P., Di Lorenzo, A., Radomski, N., & Di Pasquale, A. (2024). Veterinaria italiana, 60(4), 10.12834/VetIt.3476.23846.1.
ReporTree: a surveillance-oriented tool to strengthen the linkage between pathogen genetic clusters and epidemiological data
Mixão, V., Pinto, M., Sobral, D., Di Pasquale, A., Gomes, J. P., & Borges, V. (2023). Genome medicine, 15(1), 43.
Harmonization of supervised machine learning practices for efficient source attribution of Listeria monocytogenes based on genomic data
Castelli, P., De Ruvo, A., Bucciacchio, A., D'Alterio, N., Cammà, C., Di Pasquale, A., & Radomski, N. (2023). BMC genomics, 24(1), 560.
In vitro and in silico parameters for precise cgMLST typing of Listeria monocytogenes
Palma, F., Mangone, I., Janowicz, A., Moura, A., Chiaverini, A., Torresi, M., Garofolo, G., Criscuolo, A., Brisse, S., Di Pasquale, A., Cammà, C., & Radomski, N. (2022). BMC genomics, 23(1), 235.
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