Federico Comitani
Data Scientist, Recursion Pharmaceuticals
I am a data scientist at Recursion, developing machine learning models for structural biology and binding predictions in drug discovery. I am also a research associate in the Genetics and Genome Biology program at the Hospital for Sick Children in Toronto, working on the characterization of transcriptional heterogeneity across childhood cancers. My interests revolve around the development of translational medicine tools to bridge the gap between computational genomics, biology, and clinical practice.
I obtained my Ph.D. from King’s College London working on binding and activation mechanisms of ion channels. In the following years, I joined University College London, where I continued my work on understanding orthosteric and cryptic binding properties of complex biomolecular systems, with molecular dynamics and enhanced sampling techniques.
news
March 17, 2023 | Our paper on transcriptional heterogeneity of pediatric tumours is now available: Diagnostic classification of childhood cancer using multiscale transcriptomics |
December 30, 2022 | The KiCS, SickKids’ Cancer Sequencing Program, publication is now available on Nature Cancer: The clinical utility of integrative genomics in childhood cancer extends beyond targetable mutations |
November 23, 2022 | A new publication on hypertranscription in human cancer: Widespread hypertranscription in aggressive human cancers |
July 27, 2021 | Our new paper on the origins of leiomyosarcoma is out: Lineage-defined leiomyosarcoma subtypes emerge years before diagnosis and determine patient survival |
April 1, 2021 | Poster abstract accepted to ASCO 2021: Resolving driver events in MLL-r negative high-risk infant ALL |