Medical Systems Biology

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Boolean networks

Boolean networks are qualitative models of regulatory processes that represent the state of a node by a simple bistable switch, e.g. genes can be transcribed or not transcribed. Although being highly abstract, Boolean networks have proven to approximate the real nature of gene-regulatory processes well.

 

State graph of a Boolean network

Illustration: © 2012 Springer, Paper: M. Hopfensitz, C. Müssel, M. Maucher, and H. A. Kestler. Attractors in Boolean networks – a tutorial. Computational Statistics, 28(1):19–36, 2013.


The research of our group covers the complete process of construction, analysis and simulation of the networks. This includes approaches for the binarization of time series measurements, inference of networks from such time series, literature-based network assembly, simulation and attractor search.

 

Selected publications

 

M. Grieb, A. Burkovski, J. E. Sträng, J. M. Kraus, A. Groß, G. Palm, M. Kühl, H. A. Kestler. Predicting Variabilities in Cardiac Gene Expression with a Boolean Network Incorporating Uncertainty. PloS one, 10 (7), e0131832, 2015.

A. Naldi, P. T. Monteiro, C. Müssel, the Consortium for Logical Models and Tools, H. A. Kestler, D. Thieffry, I. Xenarios, J. Saez-Rodriguez, T. Helikar, and C. Chaouiya. Cooperative development of logical modelling standards and tools with CoLoMoTo. Bioinformatics, 31(7):1154-1159, 2015.

M. Hopfensitz, C. Müssel, M. Maucher, and H. A. Kestler. Attractors in Boolean networks – a tutorial. Computational Statistics, 28(1):19–36, 2013.

M. Hopfensitz, C. Müssel, C. Wawra, M. Maucher, M. Kühl, H. Neumann, and H. A. Kestler. Multiscale binarization of gene expression data for reconstructing Boolean networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9(2):487–498, 2012.

M. Maucher, B. Kracher, M. Kühl, and H. A. Kestler. Inferring Boolean network structure via correlation. Bioinformatics, 27(11):1529–36, 2011.

C. Müssel, M. Hopfensitz, and H. A. Kestler. BoolNet - an R package for generation, reconstruction, and analysis of Boolean networks. Bioinformatics, 26(10):1378–1380, 2010.

Latest News

 

Our paper "Interaction Empowerment in Mobile Health: Concepts, Challenges, and Perspectives" has been published in the Journal of Medical Internet Research mhealth and uhealth.

 

Our paper "Identification of dynamic driver sets controlling phenotypical landscapes" has been published in the Computational and Structural Biotechnology Journal.


Congratulations to Dr. Silke Werle for winning the 1st Prize with her pitch at the 1. Science Day held by ProTrainU. 

 

Our paper "Reconstructing Boolean network ensembles from single-cell data for unraveling dynamics in the aging of human hematopoietic stem cells" has been published in the Computational and Structural Biotechnology Journal.

 

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 "Multi-Modal Pain Intensity Assessment Based on Physiological Signals: A Deep Learning Perspective" has been published in Frontiers in Physiology.

 

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.