- author = "Christoph Muessel and Nensi Ikonomi and Silke D. Werle and Felix M. Weidner and Markus Maucher and Julian D. Schwab and Hans A. Kestler",
- title = "{CANTATA} - prediction of missing links in Boolean networks using genetic programming",
- journal = "Bioinformatics",
- year = "2022",
- volume = "38",
- number = "21",
- pages = "4893--4900",
- month = sep,
- keywords = "genetic algorithms, genetic programming",
- ISSN = "1367-4803",
-
URL = "
https://doi.org/10.1093/bioinformatics/btac623",
- eprint = "https://academic.oup.com/bioinformatics/article-pdf/38/21/4893/46697968/btac623_supplementary_data.pdf",
-
DOI = "
doi:10.1093/bioinformatics/btac623",
-
code_url = "https://github.com/sysbio-bioinf/Cantata",
- size = "8 pages",
-
abstract = "Biological processes are complex systems with distinct
behaviour. Despite the growing amount of available
data, knowledge is sparse and often insufficient to
investigate the complex regulatory behaviour of these
systems. Moreover, different cellular phenotypes are
possible under varying conditions. Mathematical models
attempt to unravel these mechanisms by investigating
the dynamics of regulatory networks. Therefore, a major
challenge is to combine regulations and phenotypical
information as well as the underlying mechanisms. To
predict regulatory links in these models, we
established an approach called CANTATA to support the
integration of information into regulatory networks and
retrieve potential underlying regulations. This is
achieved by optimizing both static and dynamic
properties of these networks. Initial results show that
the algorithm predicts missing interactions by
recapitulating the known phenotypes while preserving
the original topology and optimizing the robustness of
the model. The resulting models allow for hypothesizing
about the biological impact of certain regulatory
dependencies.
Source code of the application, example files and results are available at https://github.com/sysbio-bioinf/Cantata.
Supplementary data are available at Bioinformatics online.",
- notes = "Also known as \cite{10.1093/bioinformatics/btac623}",
