Application and development of bioinformatics and network theory methods in cardiovascular disease research and pharmacovigilance

To be able to discover novel drug targets we aim to develop software based on network theoretic approaches that are capable to identify mediators and pathways involved in the pathomechanism of various cardiovascular diseases by the analysis of datasets assessed with high throughput molecular biological techniques (e.g. microarray, RNA-seq) of samples gathered from small and large animal models of the studied cardiovascular disorders. Our main focus is the analysis of the transcriptomics datasets, including microRNA fingerprints.

Learning opportunities:

• Bioinformatics methodologies
• Analysis of raw RNA sequencing data
• Biostatistics
• Writing R and UNIX/Linux shell scripts
• Network theory

MicroRNA-target interaction network analysis: We aim to develop software based on network theoretic approaches that are capable of identifying mediators and pathways involved in the pathomechanism of various cardiovascular diseases by the analysis of datasets assessed with high throughput molecular biological techniques (e.g. microarray, RNA-seq) of samples gathered from small and large animal models of the studied cardiovascular disorders. Our main focus is the analysis of the transcriptomics datasets, including microRNA fingerprints.

Bioinformatics analysis of RNA sequencing datasets: The starting point for an unbiased, hypothesis-free analysis of various diseases is the assessment of global transcriptomics profiles. Nowadays the most well-established and most cost-effective approach for transcriptomics measurements is RNA sequencing. RNA sequencing produces huge raw datasets, which need to be analyzed by various bioinformatics methods.

Our group is continuously developing, adapting and utilizing bioinformatics and statistical methodologies to be able to better understand RNA sequencing results.

For further information or to register your interest please email pharmacology@semmelweis.hu