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Graph mining for computational biology

Computational biology data often has a complex structure. Graphs have been shown to form good representations for such interconnected data. Graph mining aims at performing data mining on such graph-structured data. Two key challenges are the computational cost of graph algorithms and the fact that samples are often not independent. Recently, progress has been made towards addressing both challenges. In this project, we will consider the specific structure of computational biology data (genomics andproteomics) and develop specialized data mining algorithms for it.

Date:3 Sep 2013  →  24 Mar 2019
Keywords:Machine learning, Mass spectrometry, Bioinformatics
Disciplines:Applied mathematics in specific fields, Computer architecture and networks, Distributed computing, Information sciences, Information systems, Programming languages, Scientific computing, Theoretical computer science, Visual computing, Other information and computing sciences
Project type:PhD project