Medical Systems Biology

You are here:  Research

Research

The rapid development of molecular biology has given rise to an increasing demand in computational and mathematical approaches to analyze and understand the resulting data. In particular, advanced methods from Bioinformatics are required to extract and investigate the essential information from high-throughput experiments, such as microarrays or Next Generation Sequencing. The emerging field of Systems Biology provides formal approaches to modeling and simulating regulatory processes in biological systems.

Research fields

Cluster analysis Molecular networks Classification Visualization & Functional annotation

The research of our group is at the interface of computer science, statistics and life sciences and covers the following main aspects:

Latest News

 

The position paper "Is there a role for statistics in artificial intelligence" has been published online first in Advances in Data Analysis and Classification.

 

Our paper "Corona Health - A Study- and Sensor-Based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic" has been published in the International Journal of Environmental Research and Public Health.

 

Our paper "Patient empowerment during the COVID-19 pandemic: Ensuring safe and fast communication of test results" has been published in the Journal of Medical Internet Research.

 

Our paper "Perspective on mHealth Concepts to Ensure Users’ Empowerment–From Adverse Event Tracking for COVID-19 Vaccinations to Oncological Treatment" has been published in IEEE Access.

 

Our paper "Capturing dynamic relevance in Boolean networks using graph theoretical measures" has been published online first in Bioinformatics.

 

Our report protocol "Digitalization of adverse event management in oncology to improve treatment outcome—A prospective study protocol" has been published in PLoS One.

 

We are happy we could contribute to Beutel et al (2021) "A prospective Feasibility Trial to Challenge Patient-Derived Pancreatic Cancer Organoids in Predicting Treatment Response" published in MDPI Cancers.