The Iorio Group works at the interface of biology, machine learning, statistics and information theory with the goal of understanding and predicting how genomic alterations and molecular traits from other omics contribute to pathological processes, biological circuits’ rewiring and have an impact on therapeutic response in human cancers and other diseases.
Our research aims at advancing human health by designing algorithms, computational tools and novel analytical methods for the integration and the analysis of pharmacogenomics and functional-genomics datasets, with the objective of identifying new therapeutic targets, biomarkers and drug repositioning opportunities.
With our experimental collaborators, we are contributing to the creation of a comprehensive map of all the genetic dependencies occurring in human cancers, and to the development of a computational infrastructure for translating this map into guidelines for early-stage drug development and precision medicine.
The Iorio Group designs, implements and maintains bioinformatics methods and original tools for the assessment of cancer pre-clinical models, the pre-processing, analysis and visualisation of genome-editing screening data, for the in-silico correction of new-technology-specific biases in such data, and for the optimization of single guide RNA libraries for pooled CRISPR-Cas9 screens and other experimental settings.
We are also interested in big-data analytics, the development of biomedical predictive models based on non-biomedical data, and computationally efficient constrained randomization strategies for testing combinatorial properties in large-scale genomic datasets and networks.
The pharmacogenomics cube (graphic concept by Francesco Iorio, illustration by Spencer Phillips, EMBL - EBI 2016 )
Iorio Group Publications
Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets
Lisa Dwane, Fiona M Behan, Emanuel Gonçalves, Howard Lightfoot, Wanjuan Yang, Dieudonne van der Meer, Rebecca Shepherd, Miguel Pignatelli, Francesco Iorio, Mathew J Garnett
2020 - Nucleic Acids Research
Analysis of CRISPR‐Cas9 screens identify genetic dependencies in melanoma
Eirini Christodoulou, Mamunur Rashid, Clare Pacini, Droop Alastair, Holly Robertson, Tim van Groningen, Amina.F.A.S Teunisse, Francesco Iorio, A.G. Jochemsen, David.J. Adams, Remco van Doorn
2020 - Pigment Cell and Melanoma Research
Drug mechanism‐of‐action discovery through the integration of pharmacological and CRISPR screens
Emanuel Gonçalves, Aldo Segura‐Cabrera, Clare Pacini, Gabriele Picco, Fiona M Behan, Patricia Jaaks, Elizabeth A Coker, Donny van der Meer, Andrew Barthorpe, Howard Lightfoot, Tatiana Mironenko, Alexandra Beck, Laura Richardson, Wanjuan Yang, Ermira Lleshi, James Hall, Charlotte Tolley, Caitlin Hall, Iman Mali, Frances Thomas, James Morris, Andrew R Leach, James T Lynch, Ben Sidders, Claire Crafter, Francesco Iorio, Stephen Fawell, Mathew J Garnett
2020 - Molecular Systems Biology
Identification of Intrinsic Drug Resistance and Its Biomarkers in High-Throughput Pharmacogenomic and CRISPR Screens
Iñigo Ayestaran, Ana Galhoz, Elmar Spiegel, Ben Sidders, Jonathan R. Dry, Frank Dondelinger, Andreas Bender, Ultan McDermott, Francesco Iorio, Michael P. Menden
2020 - Patterns
CELLector: Genomics-Guided Selection of Cancer In Vitro Models
Hanna Najgebauer, Mi Yang, Hayley E. Francies, Clare Pacini, Euan A. Stronach, Mathew J. Garnett, Julio Saez-Rodriguez, Francesco Iorio
2020 - Cell Systems
Agreement between two large pan-cancer CRISPR-Cas9 gene dependency data sets
Joshua M. Dempster, Clare Pacini, Sasha Pantel Fiona M. Behan, Thomas Green, John Krill-Burger, Charlotte M. Beaver, Scott T. Younger, Victor Zhivich, Hanna Najgebauer, Felicity Allen, Emanuel Gonçalves, Rebecca Shepherd, John G. Doench, Kosuke Yusa, Francisca Vazquez, Leopold Parts, Jesse S. Boehm, Todd R. Golub, William C. Hahn, David E. Root, Mathew J. Garnett, Aviad Tsherniak, Francesco Iorio
2019 - Nature Communications