Simone MARINI, PhD

Postdoc fellow, University of Kyoto, Japan (Since Dec 2015)

Prev: Postdoc Fellow, University of Pavia  (Jan 2013 - Dec 2015)


Room CB320 Akutsu Laboratory,

Bioinformatics Center, Institute for Chemical Research, Kyoto University,

Uji, Kyoto 611-0011, Japan.


smarini (_at) sunflower (_dot) kuicr (dot__) kyoto-u (_dot_) ac (dot_) jp

simone (_dot_) marini (at_) unipv (_dot) it

Who I am

As a scientist, I work in Bioinformatics, mainly applying Machine Learning to infer prediction models and simulations.

I worked on a wide variety of data, such as electronic health records, genomic variants, ontologies, protein sequences; and techniques, e.g. support vector machines, random forest, bayesian networks, data fusion.

My research projects span over Italy, China and Japan, and involve people working for

I lived in Pavia, Madrid, Hong Kong and Beijing. I currently live in Kyoto.


(8 institutes, 3 countries)

Technique > Matrix tri-factorization
Technology > Octave
Data > KEGG, MEROPS, Domine, Negatome, BIOGrid, Interpro, STRING

Technique > Random Forest, Burden Methods
Technology > Perl, Weka
Data > KEGG, Interpro, NGS data

Technique > Matrix tri-factorization
Technology > Octave
Data > TCGA, KEGG, GO, DO, BIOGrid, STRING, genomic variants

Technique > Dynamic Bayesian Networks, Continuous Time Bayesian Networks
Technology > MATLAB, R
Data > EDIC, DCCT, Electronic Health Records

Technique > Ensemble Learning, Cost-sensitive Learning
Technology > Perl, Weka, AJAX, Glassfish
Data > NGS, HGMD, 1TGP,  NHLBI GO Exome Sequencing Project

Technique > Markov Chain Monte Carlo, Logistic Regression
Technology > Weka, MATLAB
Data > Genotyping

Technique > Ensemble Learning, Support Vector Machines
Technology > Weka, Perl
Data > Negatome, Dscam1, Protein-interactions, Aptamers



PhD in Bioengineering

Hong Kong University of Science and Technology, China.

Thesis: Qualitative and quantitative protein interaction prediction with machine learning.


MSc in Biomedical Engineering

University of Pavia, Italy.

Thesis: Design of a classifier by coevolution of genetic algorithms and genetic programming.


BSc in Biomedical Engineering

University of Pavia, Italy.

Thesis: Bone tissue engineering, effects of mechanical shear stress on human osteoblast SAOS2.




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 2015, 57.

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)


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

*equally contributed


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, 12(7).



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


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



[to appear] Data Fusion for cleavage target prediction

Marini S, Demartini A, Vitali F, Bellazzi R, Akutsu T. Bioinformatics Italian Society National Congress 2016, podium presentation

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

Predicting Microvascular Complications from Type 2 Diabetes Retrospective Data

Sacchi L, Colombo C, Dagliati D, Marini S, Cerra C, Chiovato L, Bellazzi R. 15th Annual Diabetes Technology Meetings, 2015


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, podium presentation

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, podium presentation

PaPI: using pseudo amino acid composition to predict deleterious coding variants

Limongelli I, Marini S, Bellazzi R. Italian Bioengineering Group National Congress 2014




Outstanding contribution in reviewing, Journal of Biomedical Informatics (Elsevier)


Bioengineering Division Graduate Student Research Award, 1st ranked.


HKUST Overseas Research Award for PhD Students.



[to come in Sep] Rare disease association studies from multiple data sources. Bioengineering Division, The Hong Kong University of Science and Technology.

[to come in June] Leveraging on publicly available databases for novel peptidase target discovery. Electrical, Computer and Biomedical Engineering Dept., University of Pavia.


May 13. Motif search, sequence alignment and Support Vector Regression for Dscam protein self- and hetero-binding affinity prediction. Institute of Biophysics, the Chinese Academy of Science, Beijing.


2013 Sep, 2015 Sep

Instructor of record, University of Pavia.

Medical Informatics, 2nd year bachelor degree in Bioengineering.

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

Co-supervised 2 MSc Thesis in Molecular Biology.

Co-supervised 1 BSc Thesis in Bioengineering.

2013 Sep, 2014 Jun

High school math teacher, Pavia.

2010 Jan, 2010 Jun

Teaching assistant, The Hong Kong University of Science and Technology.

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

2007 Nov, 2008 Jun

University tutor, CESD, Italy. Private one-to-one tutoring to undergraduate and graduate students.


1. Journal of Biomedical Informatics (since 2015)

2. Briefings in Bioinformatics (since 2015)

3. Artificial Intelligence in Medicine (conferences) (since 2016)

4. American Medical Informatics Association joint Summits on Translational Science (since 2016)

5. Computers in Biology and Medicine (since 2016)

(My profile on Publons.)


Italian (Native speaker), English (Fluent), Spanish (Fluent)


2014 Jun

Software developer, DCPUK, Bangladesh. VSO Poverty Alleviation, remote services. Developement of a software to help managing dairy cooperatives.

2006 Jan, 2008, Aug

Front desk volunteer, Informagiovani, Italy. Municipal social services of Pavia.


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


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.