Characterising genotype and phenotype clonal evolution of response to therapy with Artificial Intelligence

The CDS Lab leads this 5 years AIRC-funded MFAG project, where we use Artificial Intelligence to study clonal evolution under therapy, integrating longitudinal bulk and single-cell data of haematological cancers.

Starting year and duration: 2021 (5 years). 

Fund:  My First AIRC Grant, Associazione Italiana Ricerca sul Cancro (AIRC).


Machine Learning algorithms for single-cell and long-reads sequencing

The CDS Lab leads this 2 years MUR-funded PRIN project, where we develop new machine learning algorithms for both single-cell and long-reads sequencing technologies.

Starting year and duration: 2024 (2 years). 

Fund:  PRIN PNRR 2022, Ministry of University and Research.


The EVOverse

The CDS lab and the Sottoriva lab have established EVOverse, a collaborative project between the University of Trieste and Human Technopole, to develop new Artificial Intelligence and population genetics methods to measure clonal evolution from cancer sequencing data.

Single-cell cancer evolution in the clinic

The CDS Lab collaborates to this project to combine cancer evolution modelling, new single-cell approaches and novel microfluidic devices, as well as new data integration techniques, with the aim of providing a definitive single-cell portrait of tumor cells, before and after treatment.

Starting year and duration: 2018 (5 years).  

Fund:  Accelerator Award, Associazione Italiana Ricerca sul Cancro (AIRC) and Cancer Research UK.