Livia Perfetto

Researcher (rtdB) and Assistant Professor at University of Rome, La Sapienza, Italy

livia.perfetto@uniroma1.it

Academic Appointments:

  • 2022-Present, University of Rome La Sapienza, Rome (Italy), Researcher and Assistant Professor
  • 2021-Present, University of Cambridge, Visitor Scientist
  • 2020-2022, Fondazione Human Technopole, Milan (Italy), Scientific Consultant and SIGNOR project coordinator
  • 2020-2022, European Bioinformatic Institute (EMBL-EBI), Cambridge (UK), Visitor Scientist
  • 2017-2020, European Bioinformatic Institute (EMBL-EBI), Cambridge (UK), Staff member (senior curator and bioinformatician)
  • 2016-2017, University of Rome ‘Tor Vergata’, Rome (Italy), Post-doc (AIRC personal fellowship GRANT)
  • 2014-2016, University of Rome ‘Tor Vergata’ Rome (Italy), Post-doc

Honors and Awards:

  • 2025. Awarded an Istituto Pasteur Cenci Bolognetti under 40 grant.
  • 2023. Awarded a My First AIRC grant, AIRC.
  • 2023. Awarded a PRIN PNRR 2022 grant, NextGenerationEU
  • 2022. Awarded a University of Rome, La Sapienza Seed GRANT
  • 2016. Awarded a COST action grant (within the COST Action CA15205) to organize the GREEKC Action Planning Meeting, Core Group Meeting.
  • 2015. Awarded a triennial fellowship Starwood Hotels & Resorts (AIRC grant) selected on a peer-review basis
  • 2011. Awarded a FEBS Youth Travel grant
  • 2010, Awarded 5000 € Special Prize ‘Sebastiano and Rita Raeli’ as best student of the year.

Scientific interests

From the beginning of my research I have focused on Biological Networks and on the functional insights we can gain from the analysis of physical and causal relationships between proteins. I have contributed to this general goal by looking at it from several angles. Indeed at the center of my research interests are networks of causal interactions which can provide the structure to integrate multi-omics datasets by building context-specific models that are mechanistic (can provide understanding) or predictive (can generate novel hypotheses).

Contribution to Science

During my PhD, I worked toward the development of SIGNOR, a publicly available resource of causal interactions, pathways and phenotypes embedded in the cell interactome. Since its establishment in 2015, SIGNOR has stably grown in terms data content, citations (> 250) and international collaborations. Over the years I demonstrated that data in SIGNOR could be exploited to understand the dynamics of the molecular mechanisms of diseases and to build tools for patient stratification and diagnosis in personalized medicine. I supervised the implementation of tools such as SignalingProfiler and PatientProfiler, computational strategies for multi-omics integration that combine MS-based phosphoproteomic and transcriptomic data with causal networks to derive context-specific models of cancer or drug response. In addition, I also developed ProxPath, a network-based approach contributes to identifying phenotypes that are ‘significantly close’ to a protein hit list. In summary, I explored the mechanistic links connecting the suggested gene-phenotype relations.

5 Selected publications

  • Lombardi L., Di Rocco L., Meo E., Venafra V., Di Nisio E., Perticaroli V., Nicolaeasa L.M., Cencioni C., Spallotta F., Negri R., Sacco F., Perfetto L.*. PatientProfiler: A network-based approach to personalized medicine. BiorXiv 2025
  • Venafra V, Sacco F, Perfetto L*. SignalingProfiler 2.0 a network-based approach to bridge multi-omics data to phenotypic hallmarks. NPJ Syst Biol Appl. 2024 Aug 23;10(1):95. doi: 10.1038/s41540-024-00417-6.
  • Latini S, Venafra V, Massacci G, Bica V, Graziosi S, Pugliese GM, Iannuccelli M, Frioni F, Minnella G, Marra JD, Chiusolo P, Pepe G, Helmer Citterich M, Mougiakakos D, Böttcher M, Fischer T, Perfetto L*, Sacco F. Unveiling the signaling network of FLT3-ITD AML improves drug sensitivity prediction. Elife. 2024 Apr 2;12:RP90532. doi: 10.7554/eLife.90532.
  • Iannuccelli M, Vitriolo A, Licata L, Lo Surdo P, Contino S, Cheroni C, Capocefalo D, Castagnoli L, Testa G, Cesareni G, Perfetto L*. Curation of causal interactions mediated by genes associated with autism accelerates the understanding of gene-phenotype relationships underlying neurodevelopmental disorders. Mol Psychiatry. 2024 Jan;29(1):186-196. doi: 10.1038/s41380-023-02317-3. Epub 2023 Dec 15. Erratum in: Mol Psychiatry. 2024 Jan;29(1):197. doi: 10.1038/s41380-024-02432-9.
  • Perfetto L, Briganti L, Calderone A, Cerquone Perpetuini A, Iannuccelli M, Langone F, Licata L, Marinkovic M, Mattioni A, Pavlidou T, Peluso D, Petrilli LL, Pirrò S, Posca D, Santonico E, Silvestri A, Spada F, Castagnoli L, Cesareni G. SIGNOR: a database of causal relationships between biological entities. Nucleic Acids Res. 2016 Jan 4;44(D1):D548-54. doi: 10.1093/nar/gkv1048. Epub 2015 Oct 13.

On-going Grants

Project Title Funding source Amount (Euros) Period Role of the PI
Building SigMod, a web Resource for PTM browsing and functional visualization Istituto Pasteur Italia, Fondazione Cenci Bolognetti 40.000 1/3/2025 – 28/2/2027 PI
Modelling cell communication in Pancreatic Cancer: A Systems Biology Approach to Personalized Treatments AIRC 375.452 1/1/2024 – 31/12/2029 PI (50% of time)
A systems-based approach toward personalised therapeutic strategies in Pancreatic ductal adenocarcinoma NextGenerationEU 229.498 1/12/2023 – 30/11/2025 PI (25% of time)

Complete list of published work in MyBibliography:

https://pubmed.ncbi.nlm.nih.gov/?term=livia+perfetto

KEYWORDS:

Bioinformatics, systems biology, network modelling, cancer mechanisms, database.

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