Oncogene-driven metabolic rewiring in cancer is key to allow proliferation of tumour cells in low nutrient and oxygen conditions. To study such phenomena, reconstructing context-specific metabolic models through omics data integration is crucial. Here we report the original pipeline to construct context-specific metabolic models from scRNA-seq data and we applied it to scRNA-seq data from Ewing Sarcoma.

Three types of network-based analysis of gene-gene interaction networks have been suggested and tested on the multi-omics paediatric cancer datasets. User-friendly computational environment for joint application of matrix factorization and network analysis has been implemented.

We focused on the development of patient specific signalling networks using prior knowledge about the molecular events and CRISPR perturbation datasets and associated the activity of the nodes of signalling network with drug response data to find molecular targets.

We report on the implementation of a method for multilayer community trajectory analysis and its applications, including a published study on medulloblastoma, a study on congenital myasthenic syndromes, and a study on the functional characterization of commonalities among a selection of paediatric tumours.

We report on the implementation of a method for multilayer community trajectory analysis and its applications, including a published study on medulloblastoma, a study on congenital myasthenic syndromes, and a study on the functional characterization of commonalities among a selection of paediatric tumours.

We report on the selection of the appropriate data models to handle the available data and metadata to the iPC Central Computational and Data platform. We also report on the current status of the development for the iPC Data portal.

Paper entitled: Hepatoblastomas with carcinoma features represent a biological spectrum of aggressive hepatocellular neoplasms in children and adolescents

Paper entitled: BIODICA: a computational environment for Independent Component Analysis of omics data

This paper was published at the SPIE Photonics West 2022 on 1st March 2022.

This paper was published at the SPIE Opto 2021 on 5th March 2021.

Paper entitled: A single-cell analysis of breast cancer cell lines to study tumour heterogeneity and drug response