SBI – Department of Systems Biology and Bioinformatics
Faculty of Computer Science and Electrical Engineering
University of Rostock
Ulmenstrasse 69 | 18057 Rostock
+49 381 498-7571
microRNAs and data integration - Why should we even bother?
microRNAs (miRNAs) are non-coding RNAs that post-transcriptionally regulate gene expression. They partake in diverse biological processes and have been reported to be involved in many diseases. Their expression profiles can easily be investigated since they are present in a stable form in human blood and plasma.
Therefore, what role do these tiny molecules play in the development of diseases?
To answer this question, I first analyze transcriptomics data in order to identify candidate miRNAs and genes. I then make use of data originating from various databases and of data integration methods to generate regulatory networks. After constructing these networks, I apply network analysis methods such as to uncover regulatory interactions involving miRNAs which may help us better understand the role of these molecules in diseases.
The investigations will deepen our knowledge on the impact of radiation-induced complex DNA lesions with spinoffs for radiation protection and the development of new, advanced tumor therapy strategies.
|2011 - present||
PhD: Medical Bioinformatics
|2009 - 2011||
Master of Science: Medical Biotechnology
|2009 - 2006||
Bachelor of Science: Major Physiology, Minor Physics
|Summer Semester 2006||
Guest Student: Physics
|2003 - 2005||
Diploma of College Studies: Health Science
Identification of Antineoplastic Targets with Systems Approaches, Using Resveratrol as an In-Depth Case Study.
Singh N, Freiesleben S, Wolkenhauer O, Shukla Y, Gupta SK
Curr Pharm Des. 2017;23(32):4773-4793.
Analysis of microRNA and Gene Expression Profiles in Multiple Sclerosis: Integrating Interaction Data to Uncover Regulatory Mechanisms
Sherry Freiesleben, Michael Hecker, Uwe Klaus Zettl, Georg Fuellen, Leila Tahera
Scientific Reports (2016) 6: 34512
Investigation of mammalian microRNA biogenesis by use of mathematical modeling