Chiara Damiani, P.h.D
Current Position:
Fixed-term researcher (RTD-B in INF/01) at Department of Biotechnology and BiosciencesUniversity of Milan Bicocca
Affiliated with ISBE-it/SYSBIO Center of Systems Biology
Associated editor of BMC Bioinformatics
Background:
PhD in Multiscale Modeling, Computational Simulations and Characterization in Material and Life Sciences from University of Modena and Reggio Emilia (year 2011)
Previous Positions:
Post-doc research associate at the Department of Informatics, Systems and Communication
Junior Researcher at The Microsoft Research - University of Trento Centre for Computational and Systems Biology
Visiting PhD research student under the supervision of Prof. Stuart Kauffman at Institute for Biocomplexity and Informatics, University of Calgary
Teaching:
Databases
Computer Science
Ongoing projects
Combining multi-target regression deep neural networks and kinetic modeling to predict relative fluxes in reaction systems
Selected Publications:
A. Graudenzi, Davide Maspero, Chiara Damiani*, FBCA, A Multiscale Modeling Framework Combining Cellular Automata and Flux Balance Analysis. Journal of Cellular Automata, 15(1-2):1–21, 2020.
C. Damiani*, D. Maspero, M. Di Filippo, R. Colombo, D. Pescini, A. Graudenzi, H. V. Westerhoff, L. Alberghina, M. Vanoni e 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 e 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, 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(14): i311-i318, 2017. DOI: 10.1093/bioinformatics/btx251
M. Di Filippo, R. Colombo, C. Damiani, D. Pescini, D. Gaglio, M. Vanoni, L. Alberghina, G. Mauri. Zooming in cancer metabolic rewiring with tissue specific constraint-based models. Journal of Computational Biology and Chemistry: 60-69, 2016. DOI: 10.1016/j.compbiolchem.2016.03.002
A. Paroni, A. Graudenzi, G. Caravagna, C. Damiani, G. Mauri, M. Antoniotti. CABeRNET: a Cytoscape app for Augmented Boolean models of gene Regulatory NETworks. BMC Bioinformatics, 17:64, 2016. DOI: 10.1186/s12859-016-0914-z
M. Villani, A. Filisetti, A. Graudenzi, C. Damiani, T. Carletti e R. Serra. Growth and Division in a Dynamic Protocell Model. Life, 4(4): 837-864, 2014. DOI: 10.3390/life4040837
C. Damiani, D. Pescini, R. Colombo, S. Molinari, L. Alberghina, M. Vanoni, e G. Mauri. An ensemble evolutionary constraint-based approach to understand the emergence of metabolic phenotypes. Natural Computing, 13(3): 321-331, 2014. DOI: 10.1007/s11047-014-9439-4
C. Damiani, R. Serra, M. Villani, S.A. Kauffman, e A. Colacci. Cell-cell interaction and diversity of emergent behaviours. IET Systems Biology, 5(2):137–144, 2011. ISSN 1751-8849. DOI: 10.1049/iet-syb.2010.0039.