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
Ausschreibung:
Fellowships Computational Sciences