Giuseppe Jurman

Giuseppe Jurman is a mathematician, with a PhD in Algebra, working at MPBA on various aspects of computational biology. His main research interests are statistical machine learning, mathematical modeling for high-throughtput data and network analysis. He is also an expert in scientific programming with Python and other computing languages.

1. Chierici, Marco; Giulini, Marco; Bussola, Nicole; Jurman, Giuseppe; Furlanello, Cesare,
   Machine learning models for predicting endocrine disruption potential of environmental chemicals,
   in «JOURNAL OF ENVIRONMENTAL SCIENCE AND HEALTH. PART C, ENVIRONMENTAL CARCINOGENESIS & ECOTOXICOLOGY REVIEWS»,
   vol. 36,
   n. 4,
   2019
   , pp. 237 -
   251
2. Boldrini, Renata; De Pasquale Maria, Debora; Melaiu, Ombretta; Chierici, Marco; Jurman, Giuseppe; De Benedetti Maria, Chiara; Salfi Nunzio, C; Castellano, Aurora; Collini, Paola; Furlanello, Cesare; Pistoia, Vito; Cifaldi, Loredana; Terenziani, Monica; Fruci, Doriana,
   Tumor-infiltrating T cells and PD-L1 expression in childhood malignant extracranial germ-cell tumors,
   in «ONCOIMMUNOLOGY»,
   vol. 8,
   n. 2,
   2019
3. Jurman, Giuseppe,
   Seasonal Linear Predictivity in National Football Championships,
   in «BIG DATA»,
   vol. 7,
   n. 1,
   2019
   , pp. 21 -
   34
4. Bizzego, Andrea; Bussola, Nicole; Chierici, Marco; Maggio, Valerio; Francescatto, Margherita; Cima, Luca; Cristoforetti, Marco; Jurman, Giuseppe; Furlanello, Cesare,
   Evaluating reproducibility of AI algorithms in digital pathology with DAPPER,
   in «PLOS COMPUTATIONAL BIOLOGY»,
   vol. 15,
   n. 3,
   2019
   , pp. e1006269 -
5. Jurman, Giuseppe; Filosi, Michele; Visintainer, Roberto; Riccadonna, Samantha; Furlanello, Cesare,
   Stability in GRN inference,
   Gene Regulatory Networks: Methods and Protocols, Methods in Molecular Biology,
   2019
   , pp. 323 -
   346
6. Bizzego, A.; Bussola, N.; Salvalai, D.; Chierici, M.; Maggio, V.; Jurman, G.; Furlanello, C.,
   Integrating deep and radiomics features in cancer bioimaging,
   Proceedings of 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB),
   2019
   , pp. 1-
   8
   , (2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB),
   Siena, Italy,
   9-11 July 2019)
7. Furlanello, Cesare; Jurman, Giuseppe; Dolci, Claudia; Villani, Rachele; Gadotti, Erik; Venuti, Paola,
   Talents and technology: training the artificial intelligence generation,
   Talent Education 2019,
   Ljubljana,
   MIB,
   2019
   , pp. 31-
   35
   , (IV Talent Education 2019,
   Portoroz,
   24-26 Oct 2019)
8. Mohammadian Rad, Nastaran; Kia, Seyed Mostafa; Zarbo, Calogero; van Laarhoven, Twan; Jurman, Giuseppe; Venuti, Paola; Marchiori, Elena; Furlanello, Cesare,
   Deep learning for automatic stereotypical motor movement detection using wearable sensors in autism spectrum disorders,
   in «SIGNAL PROCESSING»,
   vol. 144,
   2018
   , pp. 180 -
   191
9. Fioravanti, Diego; Giarratano, Ylenia; Maggio, Valerio; Agostinelli, Claudio; Chierici, Marco; Jurman, Giuseppe; Furlanello, Cesare,
   Phylogenetic convolutional neural networks in metagenomics,
   in «BMC BIOINFORMATICS»,
   vol. 19,
   n. S2,
   2018
10. Francescatto, Margherita; Chierici, Marco; Rezvan Dezfooli, Setareh; Zandonà, Alessandro; Jurman, Giuseppe; Furlanello, Cesare,
    Multi-omics integration for neuroblastoma clinical endpoint prediction,
    in «BIOLOGY DIRECT»,
    vol. 13,
    n. 1,
    2018
    , pp. 5 -

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