Project Score database: a resource that will help designing the next generation of anti-cancer drugs
26 October 2020
Project Score database: a resource that will help designing the next generation of anti-cancer drugs
A new paper published by Nuclear Acids Research and co-authored by Francesco Iorio, Group Leader at the Centre for Computational Biology, describes the creation of Project Score: a web portal enabling users to estimate the potential of each gene as a therapeutic target of future anti-cancer drugs.
Project Score, created and maintained by the group of Mathew Garnett at the Wellcome Sanger Institute, allows to browse data, download free datasets, and investigate specific biological hypotheses. For example, by specifying the name of any gene, the system will offer additional information on the gene’s target-priority score, potential biomarkers and tractability, including whether there are already drugs available to inhibit the corresponding coded protein.
The data underlying this resource has been made available thanks to CRISPR Cas9 whole-genome drop out screens which allow to better understand gene function and identify dependencies in cancer cells. The system is based on a computational pipeline developed by Francesco Iorio, Fiona Behan and Mathew Garnett and data described in a paper published last year in Nature, as part of the Cancer Dependency Map initiative.
PRECISE (Predictive Relationships Explaining Cancer Genetic Interactions and Synthetic Essentiality) is a pan-European initiative that aims to move cancer research beyond cataloguing cancer vulnerabilities towards predicting them before they are experimentally tested. Human Technopole (HT) is among the founding partners of the consortium, with Francesco Iorio leading its scientific activities across the institute alongside other HT research groups. The consortium and its scientific vision are presented in a Nature Genetics commentary.
Human Technopole has opened a new Call for Access to its National Facilities, offering researchers across Italy the opportunity to use advanced technologies, specialised expertise and scientific support across HT’s shared research infrastructure.
Researchers at Human Technopole have developed a novel machine learning-based method that transforms composite fluorescence microscopy images with overlapping signals into separate images revealing individual cellular structures. The tool is published in Nature Methods, with experimental models and training data openly available on GitHub.
The mechanisms of life are complex. What happens at the molecular level shapes cells, tissues, organs and entire organisms. To understand human biology, and what drives disease, we need to connect these different scales rather than study them in isolation. That is our approach at Human Technopole.
“Shaping the future of human health, together”: Human Technopole’s new claim was the central theme of the event held this morning at the Senate of the Republic. The conference “Human Technopole Foundation: a model of open research and innovation in the life sciences” provided an opportunity to present the third biennial Report to Parliament for 2024–2025, marking the Foundation’s definitive transition to a new phase of maturity.
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