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Mathematical and Learning Tools for Immunology

DIETI Contact person / Partner: Francesco Verde

Abstract

In subjects with autoimmunity (i.e., multiple sclerosis), an important aspect of the immune system is how T lymphocytes respond to T cell receptor (TCR) stimulation. This is a key event controlling the fate of naïve T lymphocytes impacting on activation, differentiation and regulation of the immune response, which has been shown to be impaired in subjects with autoimmunity. T cell responsiveness is inherently stochastic (i.e., it cannot be predicted a priori) due to different sources of noise that are intrinsically produced by the underlying biochemical reactions. Such a noise may influence T cell activation grade by degrading the information transmission from the TCR.

Objective

The aim is to help the oncologist to better understand when a change of therapy is needed through machine learning methodologies and statistical analysis of clinical variables such as the patient's medical condition, the aggressiveness of the cancer, the effectiveness of the treatments.

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Available

Can be assigned to one doctoral student of cycle XXXVI 

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