room 4024, building U3, tel.: +39 02 6448 3308

pasquale.palumbo@unimib.it

Laurea degree (1995) and Ph.D (2000) in Electronic Engineering, University of L’Aquila. Associate Professor of Automatic Control (ING/INF-04), Department of Biotechnologies and Biosciences, University of Milano-Bicocca, since 2019.

In 2000 joined the Institute of Systems Analysis and Computer Science “A. Ruberti” at the National Research Council (IASI-CNR) as a post-doc till 2005, then as a reasearcher till 2019, then as a research associate till present. In 2019 won a CNR contest as a senior researcher.

Contract Professor at the University of L’Aquila, School of Engineering, from 2000 till 2019, teaching Probability and Statistics (2000/01 and 2001/02), Automatic Control (2002/03), Systems Theory (from 2003/04 till 2006/07), Systems Biology (lessons in English, 2018/19). Supervisor of more than 80 theses (36 Master theses) concerning Systems Theory, Automatic Control, Biomathematics and Systems Biology.

Honorary Professor at Obuda University, Budapest, Hungary (since 2018).

Member of the IEEE Control Systems Society and of the IEEE Technical Committees on Systems Biology and on Healthcare and Medical Systems. Member of the Italian Association of Researchers in Automatic Control (SIDRA). Member of the Italian Society for Applied and Industrial Mathematics (SIMAI). Member of the Italian Society of Biochemistry and Molecular Biology (SIB).

Author of over 100 peer-review publications, indexed on ISI-WOS and Scopus. Recipient of the 2013 Editor's Award of the Kybernetyka Journal. Recipient of the 2018 Editor's Award of the IET Systems Biology Journal.

Member of the Editorial Board of PLoS ONE, Frontiers, Mathematical Problems in Engineering journals. Member of the Conference Editorial Board (CEB) of the IEEE Control Systems Society

Mathematical Control Theory, State estimation, Nonlinear Filtering, Stochastic Systems, Artificial Pancreas, Healthcare and Biomedical Systems, Systems Biology, Synthetic Biology, Chemical Master Equations

Scientific activity involves both methodological items, like Mathematical control theory (Polynomial method for stochastic control and filtering, Positive systems) and application items, like Mathematical modeling and control in biology and medicine (glucose-insulin models, the artificial pancreas, tumor growth control) and Systems and Synthetic Biology (Integrated models of cellular metabolism, growth and cycle, Metabolic Flux Analysis, Chemical Master Equations, noise propagation in transcriptional and metabolic networks)

-Formal Methods for the design of an Artificial Pancreas for subjects with type 2 diabetes and clinical validation
Anno: 2023
Bando: FAQC 2023 - seconda finestra
Enti finanziatori: Università degli Studi di MILANO-BICOCCA

(1) Palumbo, P., Vanoni, M., Cusimano, V., Busti, S., Marano, F., Manes, C., et al. (2016). Whi5 phosphorylation embedded in the G 1 /S network dynamically controls critical cell size and cell fate. NATURE COMMUNICATIONS, 7, 11372.

(ii) Borri, A., Palumbo, P., & Singh, A. (2016). Impact of negative feedback in metabolic noise propagation. IET SYSTEMS BIOLOGY, 10(5), 179-186.

(iii) Borri, A., Cacace, F., De Gaetano, A., Germani, A., Manes, C., Palumbo, P., et al. (2017). Luenberger-Like Observers for Nonlinear Time-Delay Systems with Application to the Artificial Pancreas: The Attainment of Good Performance. IEEE CONTROL SYSTEMS, 37(4), 33-49.

(iv) Cacace, F., Cusimano, V., & Palumbo, P. (2020). Optimal impulsive control with application to antiangiogenic tumor therapy. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 28(1), 106-117.

National Research Council (CNR)

Obuda University

University of L’Aquila

University of Delaware

Vrije University Amsterdam

Campus Bio-Medico University of Rome

Palumbo’s Lab – #PalumboLab_BtBs
last update September 2020

room 4019, building U4, tel.: +39 02 6448 3402

chiara.damiani@unimib.it

Linkedin, ResearchGate, Google Scholar, Scopus

Chiara Damiani is Assistant Professor (RTD-b) in Computer Science at the Department of Biotechnology and Biosciences of the University of Milan-Bicocca. She is associated editor of BMC Bioinformatics. She is expert in -omics data integration and modeling and simulation of biological systems.

She previously was post-doc fellow at the Department of Informatics, Systems and Communication of the University of Milano-Bicocca (2013-2019) and Junior Researcher at The Microsoft Research - University of Trento Centre for Computational and Systems Biology (2011-2012). She obtained a PhD is in Multiscale Modeling, Computational Simulations and Characterization in Material and Life Sciences from the University of Modena and Reggio Emilia. She was visiting PhD student at the Institute for Biocomplexity and Informatics (Calgary University) under the supervision of Stuart Kauffman.

Flux Balance Analysis - Metabolic networks – Sensitivity analysis – Multiscale modeling – Single-cell RNA-seq – Cancer metabolism – Data integration – Complex systems

My main research interest concerns the development of data science solutions to extract knowledge form -omics data, taking into account emergent properties arising from the interaction of the many components composing biological systems.

Main research activities: metabolic network reconstruction modeling and simulation, transcriptomics metabolomics and single-cell RNAseq data analysis, multi-omics data integration methods, multi-scale simulation of multicellular organisms and cancer cells populations.

-Computational systems biology

-Health Informatics

-Data Science

- CHRONOS (active)
- “ITFOC, Information Technology: The Future of Cancer Treatment”, within the FLAG-ERA Joint Transnational Call (JTC) 2016 (active)
- SysBioNet, a MIUR initiative for the Italian Roadmap of European Strategy Forum on Research Infrastructures (ESFRI), from 2012 to 2016 (finished)

-C. Damiani*, D. Maspero, M. Di Filippo, R. Colombo, D. Pescini, A. Graudenzi, H. V. Westerhoff, L. Alberghina, M. Vanoni and G. Mauri. Integration of single-cell RNA-seq data into population models to characterize cancer metabolism, PLoS Computational Biology, 15(2), e1006733, 2019. DOI: 10.1371/journal.pcbi.1006733

-A. Graudenzi, D. Maspero, M. Di Filippo, M. Gnugnoli, C. Isella, G. Mauri, E. Medico, M Antoniotti and C. Damiani*. Integration of transcriptomic data and metabolic networks in cancer samples reveals highly significant prognostic power. Journal of Biomedical Informatics, 87: 37-49, 2018. DOI: 10.1016/j.jbi.2018.09.010

-C. Damiani, R. Colombo, D. Gaglio, F. Mastroianni, D. Pescini, H.V. Westerhoff, G. Mauri, M. Vanoni and L. Alberghina. A metabolic core model elucidates how enhanced utilization of glucose and glutamine, with enhanced glutamine-dependent lactate production, promotes cancer cell growth: The WarburQ effect. PLoS Computational Biology, 13(9): e1005758, 2017. DOI: 10.1371/journal.pcbi.1005758

-C. Damiani*, M. Di Filippo, D. Pescini, D. Maspero, R. Colombo and G. Mauri. popFBA: tackling intratumour heterogeneity with Flux Balance Analysis. Bioinformatics, 33: i311–i318, 2017. doi: 10.1093/bioinformatics/btx251

-Hans V. Westerhoff, Manchester Centre for Integrative Systems Biology and University of Amsterdam
-Odemir M. Bruno, University of Sao Paulo
-Stuart Kauffman, Institute of Systems Biology (Seattle)
-Enzo Medico e Claudio Isella, Istituto di Candiolo – IRCCS
-Roberto Serra e Marco Villani, Università di Modena e Reggio Emilia
-Alex Graudenzi e Daniela Gaglio, Institute of Molecular Bioimaging and Physiology, Consiglio Nazionale delle Ricerche (IBFM-CNR)
-Marco Nobile, Eindhoven University of Technology
-Giulio Caravagna, Università di Trieste

Damiani’s Lab – #DamianiLab_BtBs
last update September 2020