Marini Simone

 

 

 

Dipartimento di Ingegneria Industriale e dell'Informazione

Università degli Studi di Pavia

Via Ferrata 1 27100 Pavia (Italy)

tel: +39-0382-985746

fax: +39-0382-525638

 

simone.marini (at) unipv.it

 

Current Position

Post-doc fellow. Department of Electrica, Computer and Biomedical Engineering, University of Pavia, Italy

Academic Degree

2012 PhD in Bioengineering. The Hong Kong University of Science and Technology, Hong Kong SAR, PRC.
2007 Laurea (MSc with research thesis) in Biomedical Engineering, University of Pavia, Italy.
2004 Laurea (BSc with research thesis) in Biomedical Engineering, University of Pavia, Italy.

Research Interests

I make prediction models and simulations applying several Machine Learning techniques. I work on a wide variety of data, in both Health Informatics and Bioinformatics. My most recent interest is Data Fusion, i.e. the integration of heterogeneous data sources, as well as ontologies and knowledgebases, in prediction/discovery models.
 

 Major research projects

Protein cleavage target prediction

            Technique       Matrix tri-factorization

            Technology     Octave

            Data                KEGG, MEROPS, Domine, 3did, Negatome, BioGRID, Interpro, STRING

 

NGS epilepsy multiaxial association study

            Technique       Random Forest, Burden Methods

            Technology     Perl, Weka

            Data                NGS data, KEGG, Interpro, BioGRID

 

Cohort simulation of Type 1 and 2 diabetes

            Technique       Dynamic Bayesian Networks, Continuous Time Bayesian Networks

            Technology     MATLAB, R

            Data                EDIC, DCCT, Electronic Health Records

 

Genomic variant deleteriousness prediction

            Technique       Ensemble Learning, Cost-sensitive Learning

            Technology     Perl, Weka, AJAX, Glassfish

            Data                NGS, HGMD, 1TGP, NHLBI GO Exome Sequencing Project

 

SNP selection and effects on sample mislabeling on Machine Learning

            Technique       Markov Chain Monte Carlo, Machine Learning

            Technology     Weka, MATLAB

            Data                Genotyping

 

DNA-, RNA- and protein-protein interaction (or affinity) prediction

            Technique       Ensemble Learning, Support Vector Machines

            Technology     Weka, Perl

            Data                Dscam1, Protein-interactions

More on www.simonemarini.com