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AIM – Artificial Intelligence in Medicine

 

Local Project Coordinator: Daniel Remondini
National Project Coordinator: Alessandra Retico (Pi)
Research Units: Ba, Bo, Ca, Ct, Fi, Ge, Pi
Duration: 2019-2021

Local Group : D. Remondini, L. Brizi Lonardo, G. Castellani, N. Curti, E. Giampieri,  T. Matteuzzi, A. Merlotti, C. Sala, C. Testa

The BO group involves researchers with expertise in biological Big Data analysis, Machine Learning and mathematical modelling of biological systems (Systems Biology, Network Theory, Stochastic Processes). They also work to radiomics studies (integration of PET, CT and GEP profiling) in collaboration with several centers (IRCCS Reggio Emilia, IRCCS Meldola). They are involved in several EU projects (IMI-2 Harmony, COMPARE, Propag-Ageing, ITN IMforFuture, VEO) for the analysis and management of omics data integrated with networks of knowledge (Protein, Transcriptome and Metabolic interaction networks). They collaborate directly with CNAF Computing Group for tasks of data management and High Performance Computing.

Activities where Bologna is involved include:

+ Harmonization of omic data

NGS and high-throughput data from several EU centers (inside IMI HARMONY EU project) will be studied, and will be tested against clustering and feature extraction algorithms as a function of the designed harmonization (e.g. normalization per sample/per probe) procedures.

 


+ Integrated quantification of PET and omics data

PET data available from public database and from collaborations (Ospedale S. Orsola for prostate cancer PET data) will be analyzed for associations with clinical features (e.g. response to treatments, degree of aggressiveness). When available, these observables will be combined with omics data (WES, SNP, GEP, metabolomics) to increase their explanatory power (sample classification, regression with phenotypical parameters).


+ Predictive models for Systems Medicine

Exploiting the availability of public data (e.g. ENCODE, TCGA) the group will propose models for data integration: 1) cancer drug repurposing and novel target identification; 2) relation between genomics (DNA sequence), epigenomics (histones and other chromatin remodelers) and chromatin DNA structure (hi-c and WGBS data)