Computational Health at UNIPI Corrado Priami - - PowerPoint PPT Presentation

computational health at unipi
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Computational Health at UNIPI Corrado Priami - - PowerPoint PPT Presentation

Computational Health at UNIPI Corrado Priami corrado.priami@unipi.it Alina Srbu alina.sirbu@unipi.it Health and computer science Mathematics Health Systems informatics biology Medicine Computer Physics Science Bioinformatics


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Computational Health at UNIPI

Corrado Priami corrado.priami@unipi.it Alina Sîrbu alina.sirbu@unipi.it

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Medicine Mathematics Physics Chemistry Biology

Computer Science

Health and computer science

Systems biology Computational chemistry Computational biology Bioinformatics Health informatics

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CS department UNIPI Stanford University Translational medicine

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Pediatric Acute-onset Neuropsychiatric Syndrome (PANS)

  • Recently classified disease - children suddenly develop tics, obsessive

behaviour, fears, sleep and eating disorders

Psychological? Bacterial infection? Metabolomics Proteomics Clinical history

Mechanisms of the disease still unknown!

Biomarkers Mechanisms Better therapy

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Machine learning for disease diagnosis

  • Diagnosis - classification problem

PANS data

Machine learning

PANS diagnosis IBS data

Machine learning

IBS diagnosis

Challenge deadline 15th January

RAC RAC

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Sleeping patterns and health

Activity Hormones: cortisol, melatonin, .. Food Sleep quality Stress, feelings HOW DO THEY ALL WORK TOGETHER? Wrist band data

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Dynamic models for health

Time series data Pathways Domain knowledge simulations Drug testing Drug design Disease mechanisms Dynamic computational model

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Corrado Priami corrado.priami@unipi.it Alina Sîrbu alina.sirbu@unipi.it

References 1. https://sparkglobal.io/ 2. http://www.sbvimprover.com/challenge-5 3. https://github.com/alsri/RAC 4. Lauria, M., Persico, M., Dordevic, N., Cominetti, O., Matone, A., Hosking, J., Jeffery, A., Pinkney, J., Da Silva, L., Priami, C. and Montoliu, I., 2018. Consensus Clustering of temporal profiles for the identification of metabolic markers of pre-diabetes in childhood (EarlyBird 73). Scientific reports, 8(1), p.1393. 5. Simoni, G., Reali, F., Priami, C. and Marchetti, L., 2019. Stochastic simulation algorithms for computational systems biology: Exact, approximate, and hybrid methods. Wiley Interdisciplinary Reviews: Systems Biology and Medicine. 6. Sîrbu, Alina, Martin Crane, and Heather Ruskin. "Data integration for microarrays: Enhanced inference for gene regulatory networks." Microarrays 4, no. 2 (2015): 255-269.