Smart Cities & Communities

I-CiTies 2020 6ª Conferenza annuale CINI sulle ICT per Smart Cities & Communities

Virtual Conference with participation free of charge WebSit ...

I-CiTies 2018 - Italian Conference on Smart Cities

I-CiTies 2018 - Italian Conference on Smart Cities

L'Aquila, September 19-21, 2018 ...

MONIQA

MONIQA

  Indice di Qualità dell'Aria in Italia ...

ITALIAN SMART CITIES

ITALIAN SMART CITIES

Attivato ‘Italian Smart Cities’, database nazion ...

SMART CITIES: QUALE RUOLO PER LA RICERCA?

SMART CITIES: QUALE RUOLO PER LA RICERCA?

  Convegno Inaugurale del Laboratorio Nazionale CINI ...

Informatica per le Smart Cities

Informatica per le Smart Cities

Presentato il Rapporto CINI "Informatica per le ...

Il Prof. Antonio Puliafito, nuovo direttore del Laboratorio Smart Cities & Communities

Il Prof. Antonio Puliafito, nuovo direttore del Laboratorio Smart Cities & Communities

Il Prof. Antonio Puliafito e’ stato nominato Direttore d ...

The Department of Computer Science, Università degli Studi di Milano has just concluded the European project  ParBigMen. The project lasted two years, from 2020 to 2022, and has been carried out in collaboration with the Department of Ecological and Biological Sciences (DEB) at Università della Tuscia, Viterbo, Italy, and The Jackson Laboratory for Genomic Medicine, Farmington, CT (USA).

The project aimed to discover pathogenic variants associated with genetic diseases, using Machine Learning and advanced High Performance Computing methods. In particular, the project aimed to improve the results obtained so far in the context of Mendelian diseases by using an expanded dataset. This involved very demanding computations, performed on the HPC resources of SuperMUC-NG, a HPC cluster ranked in the top 10 supercomputers in the world.

Researchers fine-tuned the Machine Learning models and successfully discovered the minimum set of genomic features in a reasonable amount of time (12 hours on the SuperMUC-NG cluster, compared to estimated 2 years on a single machine). The developed code is available at https://github.com/AnacletoLAB/parSMURF-NG.

News by prof. Giorgio Valentini, Department of Computer Science, Università degli Studi di Milano

 

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