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Dissecting the complex structure of the phenome through machine learning

Projektnummer

0054407

Zusammenfassung

Understanding phenotypic variation, and in particular identifying the causal genetic or environmental regulators, is a major aim in biological investigations. The goal of this fellowship is to develop machine learning techniques to model the structure of the underlying complex system based on modern, high-dimensional phenotype datasets. First, the temporal structure of phenotypes that are recorded over time is addressed. By statistical modelling the smoothness of time series is exploited for identifying change points. Second, the structure of images, arising when digital pictures are u...

Projektinformationen

Status:

Beendet

Startdatum:

01.05.2010

Enddatum:

31.10.2012

Fördersumme:

164.500 €

Profilbereich:

Beendete Förderinitiativen

Förderinitiative:

Neue konzeptionelle Ansätze zur Modellierung und Simulation komplexer Systeme