Simone MARINI, PhD.

Postdoctoral fellow at Akutsu Laboratory,

Bioinformatics Center, Institute for Chemical Research, Kyoto University, Japan.


Prev: Postdoctoral fellow, Laboratory for Biomedical Informatics, Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Italy.


CONTACTS

at Kyoto University:

-email: smarini (_at) sunflower (_dot) kuicr (dot_) kyoto-u (_dot) ac (dot_) jp

-office phone: +81-0774-38-3017

at University of Pavia:

-email: simone (dot_) marini (at_) unipv (_dot) it

Linkedin


PROJECTS AND RESEARCH INTERESTS


Data Fusion (Knowledge discovery in Epilepsy, Myelodysplastic syndromes and protein cleavage)

Techniques: Matrix tri-factorization, Association Study, Random Forest, Burden (Collapsing) Methods

Technologies: Matlab, High Performance Computing, Perl

Data: NGS, TCGA, TarBase, KEGG, GO, DO, MEROPS, GEO, Domine, Negatome, BIOGrid, Interpro, STRING, genomic variants


Cohort simulation (Type 1 and 2 diabetes)

Techniques: Dynamic Bayesian Networks, Continuous Time Bayesian Networks, Tabu Search

Technologies: Matlab, R

Data: EDIC, DCCT, Electronic Health Records


Genomic variant deleteriousness prediction (Classification, webtool)

Techniques: Random Forest, Ensemble Learning, Cost-sensitive Learning, Chou's Pseudo Amino Acids

Technologies: Perl, Weka, AJAX, Glassfish

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


SNP selection

Techniques: Markov Chain Monte Carlo, Logistic Regression

Technologies: Matlab, Weka

Data: Beet root, genotyping


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

Techniques: Ensemble Learning, Support Vector Machines, Random Forest, Chou's Pseudo Amino Acids

Technologies: Weka, Perl

Data: Negatome, DSCAM, Protein-interactions, Aptamers





EDUCATION AND QUALIFICATIONS

PhD in Bioengineering (2008 – 2012)
Hong Kong University of Science and Technology, Hong Kong, PRC, Bioengineering Division
Thesis: Qualitative and quantitative protein interaction prediction with machine learning.

MSc in Biomedical Engineering (2004 – 2007)
University of Pavia, Pavia, Italy.
Thesis: Design of a classifier by coevolution of genetic algorithms and genetic programming.

BSc In Biomedical Engineering (2000 - 2004)
University of Pavia, Pavia, Italy.
Thesis: Bone tissue engineering, effects of mechanical shear stress on human osteoblast SAOS2.


TEACHING AND RESEARCH EXPERIENCES

Dec 2015 – Present JSPS Postdoc fellow, University of Kyoto, Japan.

Akutsu Laboratory, Bioinformatics Center, Institute for Chemical Research.


Jan, 2013Dec 2015 Postdoc fellow , University of Pavia, Italy.

Laboratory of Biomedical Engineering “Mario Stefanelli”.


Sep, 2013 Sep 2015 Instructor of record, University of Pavia, Italy.

Medical Informatics, 2nd year bachelor degree in Bioengineering.

Automatic Learning in Medicine,1st year master degree in Bioengineering.


Sep, 2012 Jun, 2014 High school math teacher, Centro Servizi Formazione di Pavia, Italy.


Sep, 2012 – Jan, 2013 Adjunct researcher, University of Pavia, Italy.

Custom Computing and Programmable Systems Lab


Dec, 2010May, 2011 Visiting PhD student, Tsinghua University, China.

MOE Key Laboratory of Bioinformatics.


Jan, 2010 – Jun, 2010 Teaching assistant, The Hong Kong University of Science and Technology, China.

Introduction to Bioengineering, 1st year graduate school in Bioengineering.


Nov, 2007 – Jun, 2008 University tutor, CESD, Italy.

Private one-to-one tutoring to undergraduate and graduate students.


Apr, 2006 – Sep, 2006 Visiting master student, Carlos III University, Spain.

Neural Netwoks and Artificial Intelligence lab.



AWARDS
Outstanding Contribution in Reviewing (Jun 2015)
Journal of Biomedical Informatics, Elsevier.

BIEN Graduate Student Research Award (Sep 2011)
1st ranked. Provided by The Hong Kong University of Science and Technology and the Hong Kong Medical and Healthcare Device Industries Association (HKMHDIA).

Overseas Research Award for PhD Students (Nov 2010)
Provided by The Hong Kong University of Science and Technology.

VOLUNTEERING EXPERIENCES

Software Developer (Jun 2014)
Bangladesh. Debi Chowdhurani Palli Unnayan Kendra NGO, VSO Poverty Alleviation, remote services. Developement of a software to help managing dairy cooperatives in Afzalpur and Mominpur.

Front desk volunteer (Jan 2006 - Aug 2008)
Italy. Municipal social services, Pavia. Supporting immigrants, foreigners and students in job search.


peer-reviewed PUBLICATIONS

 

Learning T2D evolving complexity from EMR and administrative data using Continuous Time Bayesian Networks
Marini S, Dagliati A, Sacchi L, Bellazzi R. 9th International Joint Conference on Biomedical Engineering System and Technolgy, 2016

Predicting Microvascular Complications from Type 2 Diabetes Retrospective Data
Sacchi L, Colombo C, Dagliati D, Marini S, Cerra C, Chiovato L, Bellazzi R. American Medical Informatics Association joint Summits on Translational Science, 2016

A Dynamic Bayesian Network model for long-term simulation of clinical complications in type 1 diabetes
Marini S, Trifoglio E, Barbarini N, Sambo F, Di Camillo B, Malovini A , Manfrini M, Cobelli C , Bellazzi R. Journal of Biomedical Informatics 57 (2015): 369-376.

PaPI: pseudo amino acid composition to score human coding variants
Limongelli I, Marini S, Bellazzi R. BMC Bioinformatics 2015, 16:123

Developing a parsimonius predictor for binary traits in sugar beet (Beta vulgaris)
Biscarini F, Marini S, Stevanato P, Broccanello C, Bellazzi R, Nazzicari N. Molecular Breeding 2015, 35(10)

A genomic data fusion framework to exploit rare and common variants for association discovery.
Marini S, Limongelli I, Rizzo E, Da T, Bellazzi R. 15th Conference of Artificial Intelligence in Medicine, 2015

Matrix tri-factorization for miRNA-gene association discovery in acute myeloid leukemia
De Martini A, Marini S, Vitali F, Bellazzi R. 15th Conference of Artificial Intelligence in Medicine [Workshop], 2015


A continuous time, multivariate model to simulate Type 2 Diabetes patients trajectories
Marini S, Dagliati A, Bellazzi R. American Medical Informatics Association joint Summits on Translational Science, 2015

Improvement of Dscam homophilic binding affinity throughout Drosophila evolution
Wang G Z, Marini S, Ma X, Yang Q, Zhang X, Zhu Y. BMC Evolutionary Biology 2014, 14:186

A multivariate data-driven model to investigate the arising of complications in T2D patients
Marini S, Malavolti M, Dagliati A, Bellazzi R. 14th Annual Diabetes Technology Meeting, 2014

PaPI: the Pseudo Amino acid variant Predictor
Marini S, Limongelli I, Bellazzi R.  Bioinformatics Italian Society National Congress 2014

A novel algorithm to predict the deleteriousness of genomic coding variants
Limongelli I, Marini S, Bellazzi R. NGS (ISCB) 2014

Dynamic Bayesian Networks to simulate type I diabetes patients cohorts
Barbarini N, Bellazzi R, Cobelli C, Di Camillo B, Manfrini F, Malovini A, Marini S, Sambo F, Trifoglio E. Economics, Modelling and Diabetes: Mount Hood Challenge, 2014

PaPI: using pseudo amino acid composition to predict deleterious coding variants
Limongelli I, Marini S, Bellazzi R. Italian Bioengineering Group National Congress 2014

Predicting Microvascular Complications from Type 2 Diabetes Retrospective Data
Sacchi L,  Colombo C, Dagliati A, Marini S, Cerra C, Chiovato L, Bellazzi R. 15th Annual Diabetes Technology Meeting, 2014

The role of SwrA, DegU and P(D3) in fla/che expression in B. subtilis.
Mordini S, Osera C, Marini S, Scavone F, Bellazzi R, Galizzi A, Calvio C. PLoS One. 2013, 8(12):e85065.

In silico Protein-Protein Interaction prediction with sequence alignment and classifier stacking.
Marini S, Xu Q, Yang Q. Curr Protein Pept Sci. 2011 Nov;12(7):614-20.


Peer reviewer
For Journal of Biomedical Informatics and Briefings in Bioinformatics, AIME and AMIA conferences. My profile on Publons.


Miscellanea
Among the stuff that I like to do in my spare time, I mention (1) traveling alone, and very cheaply; (2) playing nerdy pen-and-paper role playing games; (3) (try to) learn languages, history and philosophy.


TL;DR
I make prediction models and simulations applying several Machine Learning techniques. I work on a wide variety of data (including Big Data). By leveraging on the overlapping area between Health Informatics and Bioinformatics I am learning my way towards Precision and Personalized Medicine.



(Last update: 2016 Feb 2)