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.
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.
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.
Our first quantum computing paper "Leveraging quantum computing for dynamic analyses of logical networks in systems biology" has been published in Patterns.
Our paper "Unsupervised domain adaptation for the detection of cardiomegaly in cross-domain chest X-ray images" has been published in Frontiers in Artificial Intelligence.
"Vaccine Side Effects in Health Care Workers after Vaccination against SARS-CoV-2: Data from TüSeRe:exact Study" has been published in Viruses-Basel.
"PREDICT-juvenile-stroke: PRospective evaluation of a prediction score determining individual clinical outcome three months after ischemic stroke in young adults – a study protocol" has been published in BMC Neurology.
Our paper "Federated Electronic Data Capture (fEDC): Architecture and Prototype" has been accepted for publiaction in the Journal of Biomedical Informatics.
Our paper "Efficient cross-valdation traversals in feature subset selection" has been published in Scientific Reports.
Our paper "CANTATA - prediction of missing links in Boolean networks using genetic programming" has been published in Bioinformatics.
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.