Simone MARINI, PhD

(.) Research Investigator, Li LabUniversity of Michigan (since Aug 2017)

(.) Scientific Advisor, enGenome (since Dec 2016)

smarini (_at) med (_dot_) umich (dot_) edu (Linkedin) (Twitter) (Publons) (github)


Postdoc fellow, Laboratory for Biomedical Informatics, University of Pavia (2016 - 2017)

Postdoc fellow, Laboratory of Mathematical Bioinformatics , University of Kyoto, Japan (2015 - 2016)

Postdoc fellowLaboratory for Biomedical Informatics, University of Pavia (2013 - 2015)

Last update: Jan 2019

Yeah it's me

As a scientist, I design prediction models for Molecular Biology and Medicine with Machine Learning. I am particularly interested in data integration, i.e. in developing modeling harvesting heterogeneous data such as imaging, genomics, proteomics, ontologies and knowledgebases. 

The application range of my models is broad, from DSCAM Drosophila protein affinity prediction, to simulation of clinical trajectories in diabetic patients.

My research teams span over Italy, China, Japan, and USA, involving people working for:

I am (proudly) from Voghera, Italy. I lived in Pavia (Italy), Madrid (Spain), Hong Kong (PRC), Beijing (PRC), and Kyoto (Japan). I currently live in Ann Arbor, USA.


09/2008-11/2012 PhD, Bioengineering

Qualitative and quantitative protein interaction prediction with machine learning”. Division of Bioengineering, Hong Kong University of Science and Technology, PRC.

10/2004-12/2007 MSc, Biomedical Engineering

Design of a classifier by coevolution of genetic algorithms and genetic programming”. Electrical, Computer and Biomedical Engineering department, University of Pavia, Italy

10/2000-03/2004 BSc, Biomedical Engineering

Bone tissue engineering, effects of mechanical shear stress on human osteoblast SAOS2”. Electrical, Computer and Biomedical Engineering department, University of Pavia, Italy

Peer reviewed publications

[*] denotes equal contribution.

[§] denotes corresponding (senior) authorship.



1. Protease target prediction via matrix factorization

Marini S*§, Vitali F*, Rampazzi S, Demartini A, Akutsu T. Bioinformatics, bty746

2. A comprehensive roadmap of murine spermatogenesis defined by single-cell RNA-seq

Green CD, Ma Q, Manske GL, Shami AN, Zheng X, Marini S, Moritiz L, Sultan C, Gurczynski SJ, Moore BB, Tallquist MD, Li JZ, Hammoud SS. Developmental Cell, 46(5)

3. MTGO: PPI network analysis via topological and functional module identification

Vella D, Marini S§, Vitali F, Di Silvestre D, Mauri G, and Bellazzi R. Nature Scientific Reports, 8(1)

4. Patient similarity by joint matrix tri-factorization to identify subgroups in precision oncology

Vitali F*, Marini S*, Pala D, Demartini A, Montoli S, Zambelli A, Bellazzi R. Jamia Open, 1(1).

5. Towards more accurate prediction of caspase cleavage sites: a comprehensive review of current methods, tools and features

Bao Y., Marini S, Tamura T, Kamada M, Maegawa S, Hosokawa H, Song J Akutsu T. Briefings in Bioinformatics, bby041

6. Risk factors for the development of micro-vascular complications of type 2 diabetes in a single-centre cohort of patients

Chiovato L, Teliti M, Cogni G, Sacchi L, Dagliati A, Marini S, Tibollo V, De Cata P, Bellazzi R. Diabetes and Vascular Disease Research, 1479164118780808.

7. Patient similarity for precision medicine: A systematic review

Parimbelli E, Marini S, Sacchi L, Bellazzi R Journal of Biomedical Informatics, 83

8. A variant within the FTO confers susceptibility to diabetic nephropathy in Japanese patients with type 2 diabetes

Makiko Taira, Minako Imamura , Atsushi Takahashi, Yoichiro Kamatani, Toshimasa Yamauchi, Shin-ichi Araki, Nobue Tanaka, Natalie R. van Zuydam, Emma Ahlqvist, Masao Toyoda, Tomoya Umezono, Koichi Kawai, Masahito Imanishi, Hirotaka Watada, Daisuke Suzuki, Hiroshi Maegawa, Tetsuya Babazono, Kohei Kaku, Ryuzo Kawamori, The SUMMIT Consortium, Leif C. Groop, Mark I. McCarthy, Takashi Kadowaki, Shiro Maeda. PloS one 13.12


9. Exploring Wound-Healing Genomic Machinery with a Network-Based Approach

Vitali F, Marini S§, Balli M, Grosemans H, Sampaolesi M, Lussier YA, Cusella De Angelis MG, Bellazzi R. Pharmaceuticals, 10:2

10. Dscam1 Web Server: online prediction of Dscam1 self- and hetero-affinity

Marini S*§, Nazzicari N*, Biscarini F, Wang GZ. Bioinformatics, 33:12

11. Machine learning methods to predict Diabetes complications

Dagliati A*, Marini S*, Sacchi L, Bellazzi R. Journal of Diabetes Science and Technology, 1932296817706375


12. A data fusion approach to enhance association study in epilepsy

Marini S§, Limongelli I, Rizzo E, Errichiello E, Vetro A, Tan D, Zuffardi O, Bellazzi R. Plos one, 11:12

13. “Noisy beets”: impact of phenotyping errors on genomic predictions for binary traits in Beta vulgaris

Biscarini F, Nazzicari N, Broccanello C; Stevanato P, Marini S. Plant Methods, 12:36

14. Trans-ethnic fine mapping highlights kidney-function genes linked to salt sensitivity

Anubha Mahajan, Aylin R Rodan, Thu H Le, Kyle J Gaulton, Jeffrey Haessler, Adrienne M Stilp, Yoichiro Kamatani, Gu Zhu, Tamar Sofer, Sanjana Puri, Jeffrey N Schellinger, Pei-Lun Chu, Sylvia Cechova, Natalie van Zuydam, Johan Arnlov, Michael F Flessner, Vilmantas Giedraitis, Andrew C Heath, Michiaki Kubo, Anders Larsson, Cecilia M Lindgren, Pamela AF Madden, Grant W Montgomery, George J Papanicolaou, Alex P Reiner, Johan Sundström, Timothy A Thornton, Lars Lind, Erik Ingelsson, Jianwen Cai, Nicholas G Martin, Charles Kooperberg, Koichi Matsuda, John B Whitfield, Yukinori Okada, Cathy C Laurie, Andrew P Morris, Nora Franceschini, The SUMMIT Consortium, BioBank Japan Project. The American Journal of Human Genetics 99 (3)


15. 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, Malovino A, Manfrini M, Cobelli C, Bellazzi R. Journal of Biomedical Informatics, 57

16. PaPI: pseudo amino acid composition to score human coding variants

Limongelli I, Marini S, Bellazzi R. BMC Bioinformatics, 16:123

17. 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, 35:10


18. Improvement of Dscam homophilic binding affinity throughout Drosophila evolution

Wang GZ*, Marini S*, Ma X, Yang Q, Zhang X, Zhu Y. BMC Evolutionary Biology, 14:186


19. 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, 8:12::e85065


20. In silico Protein-Protein Interaction prediction with sequence alignment and classifier stacking

Marini S, Xu Q, Yang Q. Curr Protein Pept Sci, 12:7

Conference Papers


1. 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 Technology (HEALTHINF 2016)


2. 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 Interlligence in Medicine (AIME 2016)

3. 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 (AIME 2016) [Workshop]

Conference Abstracts


1. Estimating cancer stemness with single-cell RNA sequencing

Marini S, Brooks M, Wicha M, Li J. 2019 Keystone Symposia Conference

(L1: Single Cell Biology)


2. Gene-gene interaction module identification in single-cell RNA sequencing

Marini S, Vella D, Nazzicari N, Bellazzi R. 7th International Conference on Complex Networks and Their Applications (Complex Networks 2018)

3. Gene interaction discovery in myelodysplastic syndromes

Marini S, Vitali F, Demartini A, Bellazzi R. European Conference of Human Genetics (ESHG 2018)


4. Data Fusion for cleavage target prediction

Marini S, Demartini A, Vitali F, Bellazzi R, Akutsu T. Bioinformatics Italian Society National Congress (BITS 2106)

5. 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 (AMIA 2016)

6. 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 (DTM 2016)


7. 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 (DTM 2014)

8. PaPI: the Pseudo Amino acid variant Predictor

Marini S, Limongelli I, Bellazzi R. Bioinformatics Italian Society National Congress (BITS 2014)

9. A novel algorithm to predict the deleteriousness of genomic coding variants

Limongelli I, Marini S, Bellazzi R. NGS-ISCB 2014

10. Dynamic Bayesian Networks to simulate type 1 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

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

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

Book Chapters


1. Precision oncology: a data similarity challenge

Zambelli A, Demartini A, Pala D, Vitali F, Marini S, Bellazzi R. In: E-Health e Medicina Digitale, Quaglini S, Cesarelli M, Giacomini M, Pinciroli F eds, Patron.

Awards and Fellowships

1. 11/2015-11/2016 Japanese Society for the Promotion of Science Postdoctoral Fellowship

2. 06/2015 Elsevier Outstanding contribution in reviewing

3. 10/2011 Bioengineering Division Graduate Student Research Award, 1st ranked

4. 03/2010 HKUST Overseas Research Award for PhD Students

Invited Talks (extramural)

1. 06/2018 Data exploration of single-cell landscapes. Center for Health Technologies, Pavia, Italy.

2. 10/2017 Joint data integration for precision oncology. UFHCC Topics in Cancer seminar series, University of Florida, Gainsville, FL, USA.

3. 07/2017 miRNA Bioinformatics, sequence analysis and statistical processes. Training school "Omics technologies and bioinformatics application in ME/CFS research”, University of Pavia, Pavia, Italy.

4. 01/2017 Investigating epileptogenesis with data fusion. University of Michigan, Ann Arbor, USA

5. 09/2016 Mining heterogeneous data sources to enhance association studies. University of Arizona, Tucson, USA

6. 06/2016 Leveraging on public databases for novel peptidase target discovery, University of Pavia, Pavia, Italy

7. 05/2011 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, China


Ongoing Research Support

1. 12/2018-present University of Michigan, Mcubed Program (mini-cube).

Title: Mapping diabetic foot ulcers at the single-cell level

Role: Principal Investigator

2. 12/2017-present NIH U01DA043098 (contact PI: Akil, MPI: Li)

Title: Genetics of novelty seeking and propensity for drug abuse in outbred rats

Role: Co-Investigator

3. 12/2017-present R01GM118928 (contact PI: Li, MPI: Zoellner)

Title: High-resolution map of human germline mutation patterns and inference of mutagenic mechanisms

Role: Co-Investigator

Completed Research Support

1. 9/2015-9/2016 Kyoto University

Japanese Society for the Promotion of Science funding

Role: Postdoctoral fellow

Teaching and Mentoring Experiences

University of Michigan, USA

08/2017-present Supervising 1 postdoc, 2 postgraduates and 1 undergraduate students

Kyoto University, Japan

06/2016-09/2016 Supervised 1 undergraduate student

University of Pavia, Italy

12/2018 Introduction to Single cell RNA-seq data analysis (graduate)

09/2013-09/2015 Instructor of record: Medical Informatics (undergraduate)

09/2013-09/2015 Instructor of record: Automatic Learning in Medicine (graduate)

01/2013-11/2015, 12/2016-07/2017 Supervised 7 postgraduate and 5 undergraduate students

The Hong Kong University of Technology, China

01/2010-06/2010 Teaching assistant: Introduction to Bioengineering (postgraduate)

Service to Profession

Journal Reviewer (35+ reviews)

1. 2018-present Bioinformatics

2. 2018-present Molecules

3. 2018-present Plos One

4. 2014-present Journal of Biomedical Informatics

5. 2016 Computers in Biology and Medicine

6. 2015 Briefings in Bioinformatics

Conference Reviewer (15+ reviews)

1. 2019 IEEE CMBS

2. 2016-2017 Artificial Intelligence in Medicine, AIME

3. 2016-2017 American Medical Informatics Association joint Summits on Translational Science

4. 2017 IEEE International Conference on Healthcare Informatics, ICHC

Non-Academic Work

09/2013-06/2014 High school math teacher, EU program to fight against school dropout. Centro Servizi Formazione, Pavia, Italy

11/2007-06/2008 University tutor. Private one-to-one tutoring of undergraduate and graduate students. CESD, Pavia, Italy


Italian, Native speaker

English, Fluent

Spanish, Fluent

Volunteering and community outreach

Introducing machine learning in high school

04/2017, 11/2015, 03/2013 Introduction to data science. G. Galilei high school, Voghera, Italy.05/2014,

01/2013-03/2013 Introduction to data science. Settore Istruzione e Politiche Giovanili, Pavia. Italy.

Software developer

06/2014 VSO Poverty Alleviation, remote services. Development of a software to help managing dairy cooperatives. DCPUK, Bangladesh.


06/2007-12/2013 OMP, the first copyleft-only (Creative Commons) publishing house in Italy.

Editor in Chief

08/2007-08/2008 Kronstadt, student-based local news magazine, Pavia, Italy. Monthly issued, city audience (2000 copies). One of the firsts Italian magazines distributed under Creative Commons license.

Front desk volunteer

01/2006-08/2008 City social services of Pavia, Italy. Helping immigrants with local bureaucracy and CV writing.

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Among things I like to do in my spare time, I mention here (1) traveling; (2) playing old-school, pen-and-paper role playing games; (3) enjoying learning languages, history, and philosophy.

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I apply machine learning to bioinformatics. I make prediction models and simulations by extracting knowledge from very diverse data, which I like to integrate to squeeze more information out of them.