Publications

INTERNATIONAL JOURNALS

  1. M. Di Filippo, D. Pescini, B.G. Galuzzi, M. Bonanomi, D. Gaglio, E. Mangano, L. Alberghina, M. Vanoni, C. Damiani*. INTEGRATE: Model-based multi-omics data integration to characterize multi-level metabolic regulation. PLoS Computational Biology 18(2): e1009337, 2022. DOI: https://doi.org/10.1371/journal.pcbi.1009337

  2. F. Angaroni, K. Chen, C. Damiani, G. Caravagna, A. Graudenzi, D. Ramazzotti. PMCE: efficient inference of expressive models of cancer evolution with high prognostic power. Bioinformatics, 38(3), 754-762, 2022. DOI: https://doi.org/10.1093/bioinformatics/btab717

  3. M. Di Filippo, C. Damiani, D. Pescini. GPRuler: Metabolic gene-protein-reaction rules automatic reconstruction. PLoS Computational Biology, 17(11), e1009550, 2021. DOI: https://doi.org/10.1371/journal.pcbi.1009550

  4. L. Patruno, F. Craighero, D. Maspero, A. Graudenzi, C. Damiani*. Combining multi-target regression deep neural networks and kinetic modeling to predict relative fluxes in reaction systems Information and Computation Article number 104798, 2021

  5. M. S. Nobile; V Coelho; D. Pescini; C Damiani*. Accelerated global sensitivity analysis of genome-wide constraint-based metabolic models. Bmc Bioinformatics 78, 2021. DOI: https://doi.org/10.1186/s12859-021-04002-0

  6. C. Damiani, D. Gaglio, E., Sacco, L. Alberghina & M. Vanoni. Systems metabolomics: from metabolomic snapshots to design principles. Current Opinion in Biotechnology, 63, 190-199, 2020. DOI: https://doi.org/10.1016/j.copbio.2020.02.013

  7. C. Damiani*, L. Rovida, D. Maspero, I. Sala, L. Rosato, M. Di Filippo & G. Mauri G. MaREA4Galaxy: Metabolic reaction enrichment analysis and visualization of RNA-seq data within Galaxy. Computational and Structural Biotechnology Journal, 18, 993, 2020. DOI: 10.1016/j.csbj.2020.04.008

  8. D. Maspero, M. Di Filippo, C. Damiani, G. Caravagna, R. Colombo, D. Ramazzotti, M. Antoniotti, A. Graudenzi, M. Vanoni and D. Pescini. The influence of nutrients diffusion on a metabolism-driven model of a multi-cellular system. Fundamenta Informaticae, 171. 1-4. 279-295, 2020. DOI: 10.3233/FI-2020-1883

  9. A. Graudenzi, Davide Maspero, Chiara Damiani*, FBCA, A Multiscale Modeling Framework Combining Cellular Automata and Flux Balance Analysis. Journal of Cellular Automata, Vol. 0, pp. 1–21, 2019.

  10. 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

  11. 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

  12. R. Colombo, C. Damiani, D. Gilbert, M. Heiner, G. Mauri and D. Pescini. Emerging ensembles of kinetic parameters to characterize observed metabolic phenotypes. BMC Bioinformatics, 19(7):251, 2018. DOI: 10.1186/s12859-018-2181-7

  13. 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 #Impact Factor 2017: 4.542

  14. 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: 10.1371/journal.pcbi.1005758 #Impact Factor 2017: 7.307

  15. D. Gaglio, S. Valtorta, M. Ripamonti, M. Bonanomi, C. Damiani, S. Todde, A. S. Negri, F. Sanvito, F. Mastroianni, A. Di Campli, G. Turacchio, G. Di Grigoli, S. Belloli, A. Luini, M. C. Gilardi, L. Alberghina, R. M. Moresco. Divergent in vitro/in vivo responses to drug treatments of highly aggressive NIH-Ras cancer cells: A PET imaging and metabolomics-mass-spectrometry study. Oncotarget, 2016. DOI: 10.18632/oncotarget.10470 #5-Year Impact Factor: 6.368.

  16. M. Villani, D. Campioli, C. Damiani*, A. Roli, A.Filisetti, R. Serra. Dynamical regimes in non-ergodic random Boolean networks. Natural Computing. 1-11, 2016. DOI: 10.1007/s11047-016-9552-7 #2015 Impact Factor: 1.31

  17. 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 #2015 Impact Factor: 1.014.

  18. 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 #2015 Impact Factor: 2.435

  19. 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

  20. P. Cazzaniga, C. Damiani, D. Besozzi, R. Colombo, M.S. Nobile, D. Gaglio e M. Vanoni. Computational Strategies for a System-Level Understanding of Metabolism. Metabolites, 4(4):1034-1087, 2014. DOI: 10.3390/metabo4041034. Citations: 8 (source Google Scholar)

  21. R. Serra, A. Filisetti, M, Villani, A. Graudenzi, C. Damiani e T. Panini. A stochastic model of catalytic reaction networks in protocells. Natural Computing, 13(3): 367-377, 2014. DOI: 10.1007/s11047-014-9445-6 #2015 Impact Factor: 1.31.

  22. 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 #2015 Impact Factor: 1.31.

  23. C. Damiani*, A. Filisetti, A. Graudenzi, e P. Lecca. Parameter sensitivity analysis of stochastic models: Application to catalytic reaction networks. Computational Biology and Chemistry, 42:5–17, February 2013. ISSN 1476-9271. DOI: 10.1016/j.compbiolchem.2012.10.007. #2015 Impact Factor: 1.014.

  24. 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. #2015 Impact Factor: 1.059.

  25. Graudenzi, R. Serra, M. Villani, C. Damiani, A. Colacci, e S. A. Kauffman. Dynamical properties of a Boolean model of gene regulatory network with memory. Journal of Computational Biology, 18(10):1291–303, 2011. DOI: 10.1089/cmb.2010.0069 #2015 Impact Factor: 1.537.

ITALIAN JOURNLAS

  1. R. Serra, M. Villani, C. Damiani, A. Graudenzi, e A. Colacci. Comunicazione cellulare, livelli e strutture ordinate. Sistemi Intelligenti, 2(209-220), 2008. ISSN 1120-9550. DOI: 10.1422/27403.

LECTURE NOTES IN COMPUTER SCIENCE

  1. C. Damiani, D. Pescini & M. S. Nobile. Global Sensitivity Analysis of Constraint-Based Metabolic Models. In International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, Lecture Notes in Computer Science 11925:179-186, 2018. Springer, Cham. DOI: https://doi.org/10.1007/978-3-030-34585-3_16

  2. A. Graudenzi, D. Maspero e C. Damiani*. Modeling Spatio-Temporal Dynamics of Metabolic Networks with Cellular Automata and Constraint-Based Methods. In: G. Mauri, S. El Yacoubi, A. Dennunzio, K. Nishinari, L. Manzoni (eds) Cellular Automata. ACRI 2018. Lecture Notes in Computer Science, 11115:16-29, 2018. Springer, Cham. DOI:10.1007/978-3-319-99813-8_2

  3. R. Colombo, C. Damiani, G. Mauri, Dario Pescini. Constraining mechanism based simulations to identify ensembles of parametrizations to characterize metabolic features. In: Bracciali A., Caravagna G., Gilbert D., Tagliaferri R. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016. Lecture Notes in Computer Science (Lecture Notes in Bioinformatics), 10477:107-117, Springer, Cham, 2017. DOI: 10.1007/978-3-319-67834-4_9

  4. F. Cumbo, M. Nobile, C. Damiani, R. Colombo, G. Mauri e P. Cazzaniga. COSYS: A Computational Infrastructure for Systems Biology. In: Bracciali A., Caravagna G., Gilbert D., Tagliaferri R. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016. Lecture Notes in Computer Science (Lecture Notes in Bioinformatics), 10477:82-92, Springer, Cham, 2017. DOI: 978-3-319-67834-4_7

  5. C. Damiani*, S. A. Kauffman, R. Serra, M. Villani, e A. Colacci. Information transfer among coupled random Boolean networks. In S. Bandini, H.Umeo, S.Manzoni, e G.Vizzari, editors, Cellular Automata, 9th International Conference on Cellular Automata for Research e Industry, (ACRI 2010, Ascoli Piceno, 21-24 settembre), volume 6350/2010 of Lecture Notes in Computer Science, pages 1–11. Springer-Verlag Berlin Heidelberg, 2010. DOI: 10.1007/978-3-642-15979-4_1

  6. R. Serra, M. Villani, C. Damiani, A. Graudenzi, e A. Colacci. The diffusion of perturbations in a model of coupled random Boolean networks. In H. Umeo, S. Morishiga, K. Nishinari, T. Komatsuzaki, e S. Bandini, editors, Cellular Automata (proceedings of 8th International Conference on Cellular Auotomata ACRI 2008, Yokohama, settembre 2008), volume 5191/2008, pages 315– 322, Berlin, 2008. Springer Lecture Notes in Computer Science. ISBN 0302-9743. DOI: 10.1007/978-3-540-79992-4_40

  7. R. Colombo, C. Damiani, G. Mauri, Dario Pescini. Constraining Mechanism Based Simulations to Identify Ensembles of Parametrizations to Characterize Metabolic Features. In: Bracciali A., Caravagna G., Gilbert D., Tagliaferri R. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016. Lecture Notes in Bioinformatics 10477 pp 107-117. 2017. Springer, Cham. DOI: 10.1007/978-3-319-67834-4_9

  8. F. Cumbo, M. Nobile, C. Damiani, R. Colombo, G. Mauri e P. Cazzaniga. COSYS: A Computational Infrastructure for Systems Biology. . In: Bracciali A., Caravagna G., Gilbert D., Tagliaferri R. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016. Lecture Notes in Bioinformatics 10477, pp 82-92. 2017. Springer, Cham. DOI: 10.1007/978-3-319-67834-4_7

COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE

  1. D. Maspero, A. Graudenzi, S. Singh, D. Pescini, G. Mauri, M. Antoniotti e C. Damiani*#. Synchronization Effects in a Metabolism-Driven Model of Multi-cellular System in Artificial Life and Evolutionary Computation Communications in Computer and Information Science, 900: 115-126, Springer, Cham, 2019. DOI: https://doi.org/10.1007/978-3-030-21733-4_9

  2. C. Damiani*, R. Colombo, M. Di Filippo, D. Pescini, G. Mauri (2017). Linking alterations in metabolic fluxes with shifts in metabolite levels by means of kinetic modeling. In: Rossi F., Piotto S., Concilio S. (eds) Advances in Artificial Life, Evolutionary Computation, and Systems Chemistry. WIVACE 2016. Communications in Computer and Information Science, vol 708. pp 138-148. 2017. Springer, Cham. DOI: 10.1007/978-3-319-57711-1_12

  3. M. Di Filippo, C. Damiani, R. Colombo, D. Pescini, D., and G. Mauri (2017). Constraint-Based Modeling and Simulation of Cell Populations. In: Rossi F., Piotto S., Concilio S. (eds) Advances in Artificial Life, Evolutionary Computation, and Systems Chemistry. WIVACE 2016. Communications in Computer and Information Science, vol 708. pp 126-137 2017. Springer, Cham DOI: 10.1007/978-3-319-57711-1_11

  4. A. Graudenzi, C. Damiani*, A. Paroni, A. Filisetti, M. Villani, R. Serra e M. Antoniotti. Investigating the role of network topology and dynamical regimes on the dynamics of a cell differentiation model. Proceedings of Wivace 2014, Italian Workshop on Artificial Life and Evolutionary Computation, 14-15 maggio 2014, Vietri sul Mare, Salerno, Italy. In Advances in Artificial Life and Evolutionary Computation, Communications in Computer and Information Science 445:151-168. 2014 Springer International Publishing. DOI: 10.1007/978-3-319-12745-3_13 Citations: 1 (source Google Scholar).

  5. A. Filisetti, M. Villani, C. Damiani, A. Graudenzi, A. Roli, W. Hordijk, e R: Serra. On RAF sets and autocatalytic cycles in random reaction networks. Proceedings of Wivace 2014, Italian Workshop on Artificial Life and Evolutionary Computation, 14-15 maggio 2014, Vietri sul Mare, Salerno, Italy. In Advances in Artificial Life and Evolutionary Computation, Communications in Computer an Information Science 445:113-126. Springer International Publishing. DOI: 10.1007/978-3-319-12745-3_10 2014

CONFERENCE PROCEEDINGS

  1. F. Angaroni, C. Damiani, G. Ramunni, M. Antoniotti. Optimal Control of a Discrete Time Stochastic Model of an Epidemic Spreading in Arbitrary Networks. In 2021 Annual Modeling and Simulation Conference (ANNSIM) (pp. 1-12). IEEE 2021. DOI: 10.23919/ANNSIM52504.2021.9552097

  2. Filisetti, A. Graudenzi, C. Damiani, M. Villani, e R. Serra. The role of backward reactions in a stochastic model of catalytic reaction network. In Liò Pietro, Miglino Orazio, Nicosia Giuseppe, Nolfi Stefano, e Pavone Mario (editors), Advances in Artificial Life ECAL 2013 2-6 settembre 2013, Taormina, Italy Proceedings of the twelfth European Conference on the Synthesis e Simulation of Living Systems, page number 793. MIT press, 2013. DOI: 10.7551/978-0-262-31709-2-ch114.

  3. C. Damiani, A. Filisetti, A. Graudenzi, M. Villani, e R. Serra. Recent developments in research on catalytic reaction networks. In Alex Graudenzi, Giulio Caravagna, Giancarlo Mauri, e Marco Antoniotti, editors, EPTCS 130 Proceedings of Wivace 2013 - Italian Workshop on Artificial Life and Evolutionary Computation. Milan, Italy, 1-2 july 2013. EPCTS, 2013. DOI: 10.4204/EPTCS.130.

  4. C. Damiani e P. Lecca. Model identification using correlation-based inference and transfer entropy estimation. Proceedings of the UKSIM 5th European Symposium on Computer Modeling and Simulation, EMS 2011, Madrid, 16-18 November, 2011, 0:129–134. IEEE 2011. ISBN 978-1-4673-0060-5. DOI: 10.1109/EMS.2011.58

  5. A. Graudenzi, R. Serra, M. Villani, C. Damiani, A. Colacci, e S. A. Kauffman. Timing of molecular processes in a synchronous Boolean model of genetic regulatory network. In Proceedings of the European Conference on Complex Systems, ECCS 09, Warwick 21-25 settembre, 2009.

  6. C. Damiani, A. Graudenzi, R. Serra, A. Colacci M. Villani, e S. A. Kauffman. On the fate of perturbations in critical random Boolean networks. In Proceedings of the European Conference on Complex Systems, ECCS 09, Warwick 21-25 September, 2009.

  7. C. Damiani, A. Graudenzi, e M. Villani. How critical random Boolean networks may be affected by the interaction with others. In M. Villani R. Serra e I. Poli, editors, Artificial Life and evolutionary computation, proceeding of WIVACE 2008, pg. 271–283. World Scientific, 2008. ISBN 978-981-4287-44- 9.

  8. C. Damiani, M. Villani, Ch. Darabos, e M. Tomassini. Dynamics of interconnected Boolean networks with scale-free topology. In M. Villani R. Serra e I. Poli, editors, Artificial Life and evolutionary computation, proceeding of WIVACE 2008, Venice, 8-10 September 2008, pg. 271–283. World Scientific, 2008. ISBN 978-981-4287-44- 9.

  9. R. Serra, M. Villani, C. Damiani, A. Graudenzi, P. Ingrami, e A. Colacci. Investigating cell criticality. In G. Minati e A. Pessa, editors, Towards a general theory of emergence, pages 271–283. World Scientific, 2007.

  10. R. Serra, M. Villani, C. Damiani, A. Graudenzi, A. Colacci, e S. A. Kauffman. Interacting random Boolean networks. In J. Jost e D. Helbing, editors, Proceedings of ECCS07: European Conference on Complex Systems, paper 35, 2007.

PHD THESIS

  1. C. Damiani. Dynamics of Interacting Genetic Networks. PhD thesis within the PhD school Multiscale Modelling, Computational Simulations and Characterization in Material and Life Sciences, Modena and Reggio Emilia University. Supervisor: Claudio Giberti. Co-supervisor: Roberto Serra. 2011.

BOOK CHAPTERS

  1. M. Di Filippo, C. Damiani, M. Vanoni, D. Maspero, G., Mauri, L. Alberghina and D. Pescini, Single-cell digital twins for cancer preclinical investigation. In Metabolic Flux Analysis in Eukaryotic Cells, 331-343, 2020. DOI: 10.1007/978-1-0716-0159-4_15

  2. G. De Sanctis, R. Colombo, C. Damiani, E. Sacco, M. Vanoni. Omics and clinical data integration. In “Integration of omics approaches and systems biology for clinical applications. (in press)

  3. C. Damiani*. Modelling the influence of cell signaling on the dynamics of gene regulatory networks. In Paola Lecca, editor, Biomechanics of Cells and Tissues, volume 9 of Lecture Notes in Computational Vision and Biomechanics, pages 103–130. Springer Netherlands, 2013. ISBN 978-94-007-5889- 6. doi: 10.1007/978-94-007-5890-2_5

ABSTRACT BOOKS

  1. C. Damiani, R. Colombo, D. Paone, G. Mauri and D. Pescini. Relevant fluxes in metabolic steady-states. WIVACE 2017 book of abstracts, 2017.

  2. C. Damiani, R. Colombo, M. Di Filippo, D. Pescini and G. Mauri, Linking alterations in metabolic fluxes with shifts in metabolite levels by means of kinetic modeling, WIVACE/BIONAM 2016 book of abstracts, 2016.

  3. M. Di Filippo, Chiara Damiani, Riccardo Colombo, Dario Pescini and G. Mauri, Constraint-based Modeling and Simulation of Cell Populations, WIVACE/BIONAM 2016 book of abstracts, 2016.

  4. C. Damiani, R. Colombo, M. Di Filippo, D. Gaglio, F. Mastroianni, D. Pescini, H. V. Westerhoff, G. Mauri, M. Vanoni e L. Alberghina Unraveling the design principles of cancer metabolic with constraint-based modeling. Proceedings of FISV 2016 XIV Congress of the Italian Federation of Life Sciences, Roma, 20-23 September, 2016.

  5. R. Colombo, C. Damiani, M. Di Filippo, D. Pescini, D. Gaglio, L. Alberghina, M. Vanoni, e G. Mauri. Constraint-based approaches to investigate heterogeneity of metabolic phenotypes. Proceedings of BITS 2015, Twelfth Annual Meeting of the Bioinformatics Italian Society- University of Milan "Bicocca", 3-5 June, 2015.

  6. C. Damiani, R. Colombo, S. Molinari, D. Pescini, D. Gaglio, M. Vanoni, L. Alberghina, e G. Mauri. An ensemble approach to the study of the emergence of metabolic and proliferative disorders via flux balance analysis (abstract). In Alex Graudenzi, Giulio Caravagna, Giancarlo Mauri, e Marco Antoniotti, editors, EPTCS 130 Proceedings of Wivace 2013 - Italian Workshop on Artificial Life e Evolutionary Computation. Milano, 1-2 July, 2013, 2013. DOI: 10.4204/EPTCS.130.

  7. R. Serra, A. Filisetti, A. Graudenzi, C. Damiani, e M. Villani. A model of protocell based on the introduction of a semi-permeable membrane in a stochastic model of catalytic reaction networks. In Alex Graudenzi, Giulio Caravagna, Giancarlo Mauri, e Marco Antoniotti, editors, EPTCS 130 Proceedings of Wivace 2013 - Italian Workshop on Artificial Life and Evolutionary Computation. Milano, 1-2 july, 2013, 2013. DOI: 10.4204/EPTCS.130.

  8. M. Fedeli, T. A. Renzi, D. Morpurgo, T-P. Nguyen, C. Damiani, G. Rossetti, M. Pagani, S. Abrignani, P. Dellabona, e G. Casorati. mirna control of the gene expression program controlling inkt cell development (abstract). In Proceedings del 6th International Symposium on CD1 and NKT Cells, Gleacher Center, Chicago, IL USA, 23 -27 September, 2011.

POSTERS

  1. M. Di Filippo, R. Colombo, C. Damiani, D. Pescini, D. Gaglio, M. Vanoni, L. Alberghina, G. Mauri Zooming-in on cancer metabolic rewiring with tissue specific constraint-based models, e 17th International Conference on Systems Biology (ICSB 2016), Barcelona, 16-20 September, 2016.

  2. C. Damiani, R. Colombo, D. Pescini, M. Di Filippo, Marco Vanoni, G. Mauri, L. Alberghina, A computational strategy to investigate alternative metabolic responses to the same stimulus, 58th National Meeting of the Italian Society of Biochemistry and Molecular Biology, Urbino, 14-16 September, 2015.

  3. R. Colombo, C. Damiani, D. Pescini, M. Di Filippo, L. Alberghina, M. Vanoni, G. Mauri, Constraint-based approaches to investigate heterogeneity of metabolic phenotypes, BITS 2015, Twelfth Annual Meeting of the Bioinformatics Italian Society, Milano, 3-5 June, 2015.

  4. R. Serra, A. Filisetti, M. Villani, A. Graudenzi e C. Damiani, Stochastic dynamics of chemical reaction networks in a stylized protocell model, ECCS'14, European Conference on Complex systems, Lucca, 22-26 September, 2014.

  5. C. Damiani, D. Pescini, R. Colombo, S. Molinari, M. Vanoni, L. Alberghina, G. Mauri, Ensemble evolutionary flux balance analysis for metabolic network modeling, BITS2014, Eleventh Annual Meeting of the Bioinformatics Italian Society, Roma, February 26-28, 2014.

  6. R. Colombo, C. Damiani, D. Gaglio, D. Pescini, G. Mauri, E. Sacco, S. Molinari, L. Alberghina, e M. Vanoni. Flux balance analysis approaches towards the definition of cancer-specific metabolic rewiring, ICSB2013 - 14th International Conference on Systems Biology, Copenhagen, 29 agosto – 4 September, 2013.

  7. C. Damiani An ensemble approach to the study of the emergence of the Warburg effect via flux balance analysis, Technology and Human Health: Advances in Systems Medicine, Palmstedtsalen, Chalmers, 29 August 2013.

  8. M. Fedeli, V. Milli, T. A. Renzi, D. Morpurgo, T-P. Nguyen, C. Damiani, G. Rossetti, M. Pagani, S. Abrignani, P. Dellabona, e G. Casorati. miRNA regulation of INKT cell development, Milan meets immunology 2, IFOM-IEO campus, Milan 23 April, 2012.

  9. M. Fedeli, T. A. Renzi, D. Morpurgo, T-P. Nguyen, C. Damiani, G. Rossetti, M. Pagani, S. Abrignani, P. Dellabona, G. Casorati. miRNA regulation of the gene expression program controlling INKT cell development, Milan meets immunology 1, San Raffaele Scientific Institute, Milano, 20 September, 2011.