New technologies used to characterize health and disease status are giving us an unprecedented level of information, derived from multiple measurements of several biological samples in every single subject.

 

One of the major difficulties when trying to analyze these kind of data is handling with the complexities inherent to all biological systems, which is compounded by the increasing order of magnitude of the amount of information to be stored and analyzed.

 

The main aim of the members of info4CURE is to implement computational strategies that allow us to accelerate the selection of molecules with potential therapeutic effect in the field of personalized medicine, with special consideration to high-cost therapeutical orphan diseases or those ones with a high prevalence among the society.

 

A secondary step is to transform descriptive information into inferential models with clinical value to classify subtypes of disease, identifing biological markers, establishing mechanisms of action or predicting drug response.

 

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