Stampa la pagina Condividi su Google Condividi su Twitter Condividi su Facebook Mario Rosario Guarracino

Statistica Learning and Data Mining

Present position: Tenure track assistant professor, Department of Economics and Law, University of Cassino and Southern Lazio

Education: Ph.D in Mathematics, M.sc. Applied Mathematics

Research interest: Data Science, Artificial Intelligence, Statistical Learning Theory

Awards/Scientific Positions:
July 2020 – date:  Chief Scientific Officer,
Laboratory of Algorithms and Technologies for Network Analysis (LATNA),
National Research University Higher School of Economics (HSE), Nizhny Novgorod, Russia

Jan. 2016 – Nov. 2018: Head of the "Laboratory of Computational and Data Science,"
National Reserch Council of Italy

Jan. 2014 – De. 2018: International team member 
Laboratory of Algorithms and Technologies for Network Analysis (LATNA)
National Research University Higher School of Economics (HSE), Nizhny Novgorod, Russia.

Jan. 2012 – Dec. 2015: Head of the "Laboratory of Genomics, Proteomics, and Transcriptomics"
National Research Council of Italy 

Jan. 2007 – Dec. 2011: Head of the "Integrated Support Systems for Omics Sciences" research group
National Research Council of Italy

Jan. 2008 – date:  Affiliated researcher
"Francesco Severi" National Institute of High Mathematics (INDAM)

Jan. 2005 – Dec. 2013: Affiliated Faculty
Center for Applied Optimization,
University of Florida

Dec. 1997 – Nov. 2019: Staff researcher 
Institute for High Performance Computing and Networking
National Research Council of Italy

Memberships/Refereeing for Journals:
Springer Nature: Optimization Methods and Software, Annals of Mathematics and Artificial Intelligence, Annals of Operations Research, Journal of Optimization Theory and Applications, Journal of Global Optimization.
Elsevier: Knowledge-Based Systems,  Artificial Intelligence in Medicine,  
IEEE: Transactions on Knowledge and Data Engineering, Transactions on Computational Biology and Bioinformatics.

Main Publications:

I. Granata, M. Manzo, A. Kusumastuti, MRG, Learning from metabolic networks: current trends and future directions for precision medicine. In: Current Medicinal Chemistry (2020) DOI: 10.2174/0929867328666201217103148. 

I. Granata, MRG, V. A. Kalyagin, L. Maddalena, I. Manipur, and P. M. Pardalos. Model simplification for supervised classification of metabolic networks. In: Annals of Mathematics and Artificial Intelligence 88.1 (2020), pp. 91–104. 

I. Manipur, I. Granata, L. Maddalena, and MRG. Clustering analysis of tumor metabolic networks. In: BMC Bioinformatics 21.10 (2020), pp. 1–14.

L. Antonelli, MRG, L. Maddalena, M. Sangiovanni. Integrating imaging and omics data: a review. Biomedical Signal Processing and Control (2019) 52, 264-280.     

M. Viola, M. Sangiovanni, G. Toraldo, MRG. Semi-supervised generalized eigenvalues classification. Annals of Operations Research (2019) 276 (1-2), 249-266.

M. Sangiovanni, I. Granata, A. Thind, MRG. From trash to treasure: detecting unexpected contamination in unmapped NGS data. BMC Bioinformatics (2019) 20 (4), 168.

A. S. Thind, K. P. Tripathi, and MRG. RankerGUI: A Computational Framework to Compare Differential Gene Expression Profiles Using Rank Based Statistics. In: The International Journal of Molecular Sciences 20.23 (2019), p. 6098.

I. Granata, E. Troiano, M. Sangiovanni, MRG. Integration of transcriptomic data in a genome-scale metabolic model to investigate the link between obesity and breast cancer. BMC Bioinformatics (2019) 20 (4), 162.

MRG, L. Maddalena. SDI+: A novel algorithm for segmenting dermoscopic images. IEEE Journal of Biomedical and Health Informatics (2019) 23 (2), 481-488.

K.P. Tripathi, M. Piccirillo, MRG. An integrated approach to infer cross-talks between intracellular protein transport and signaling pathways. BMC Bioinformatics 19 (2), 58. Doi:10.1186/s12859-018-2036-2. 2018.

M. Giordano, K.P. Tripathi, MRG. Ensemble of rankers for efficient gene signature extraction in smoke exposure classification. BMC Bioinformatics 19 (2), 48. doi:10.1186/s12859-018-2035-3. 2018.

MRG, L. Maddalena. SDI+: a Novel Algorithm for Segmenting Dermoscopic Images. IEEE Journal of Biomedical and Health Informatics. doi: 10.1109/JBHI.2018.2808970. online 2018, 23.2 (2019), pp. 481–488

V. Belcastro, C. Poussin, Y. Xiang, M. Giordano, K.P. Tripathi, A. Boda, A.T. Balci, I. Bilgen, S.K. Dhanda, Z. Duan, X. Gong, R. Kumar, R. Romero, O.S. Sarac, A.L. Tarca, P. Wang, H. Yang, W. Yang, C. Zhang, S. Boué, MRG, F. Martin, M.C. Peitsch, J. Hoeng. The sbv IMPROVER Systems Toxicology computational challenge: Identification of human and species-independent blood response markers as predictors of smoking exposure and cessation status. Computational Toxicology, online 2017 (https://doi.org/10.1016/j.comtox.2017.07.004.), 5 (2018), pp. 38–51

M. Viola, M. Sangiovanni, G. Toraldo, MRG. Semi-supervised generalized eigenvalues classification. Annals of Operations Research, 1-18, (doi:10.1007/s10479-017-2674-1) online,2017, 276.1-2 (2019), pp. 249–266.

G. Felici, KP Tripathi, D. Evangelista, MRG. A mixed integer programming-based global optimization framework for analyzing gene expression data. Journal of Global Optimization, 1-18, (doi:10.1007/s10898-017-0530-0) 2017.

M. Viola, M. Sangiovanni, G. Toraldo, MRG. A Generalized Eigenvalues Classifier with Embedded Feature Selection, Optimization Letters, 11(2) 299-311, Springer, (doi:10.1007/s11590-015-0955-7) 2017.

I. Granata, M. Sangiovanni, F. Maiorano, M. Miele, MRG. Var2GO: a web-based tool for gene variants selection. BMC Bioinformatics 17 (1197), 2016.

A. Jakaitiene, M. Avino, MRG. Beta-Binomial Model for the Detection of Rare Mutations in Pooled Next-Generation Sequencing Experiments. (doi:10.1089/cmb.2016.0106) Journal of Computational Biology, 24(4): 357-367, 2016.

D. Evangelista, K.P. Tripathi, MRG. An Atlas of annotations of Hydra vulgaris transcriptome. 17 (11), 360, BMC Bioinformatics, 2016.

[Ultima modifica: martedì 19 gennaio 2021]