Research interests

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Breitwieser, L., Hesam, A., Montigny, J., Vavourakis, V., Iosif, A., Jennings, J., Kaiser, M., Manca, M., Di Meglio, A. and Al-Ars, Z., Rademakers, F., Bauer, R. 2021. BioDynaMo: an agent-based simulation platform for scalable computational biology research. Bioinformatics.

Bauer, R., Clowry, G.J. and Kaiser, M., 2021. Creative destruction: a basic computational model of cortical layer formation. Cerebral Cortex31(7), pp.3237-3253.

Pegah Kassraian-Fard, Michael Pfeiffer, Roman Bauer.  A generative growth model for thalamocortical axonal branching in primary visual cortex. PLoS Computational Biology, 2020

Peraza, L.R., Díaz-Parra, A., Kennion, O., Moratal, D., Taylor, J.P., Kaiser, M., Bauer, R. and Alzheimer's Disease Neuroimaging Initiative, 2019. Structural connectivity centrality changes mark the path toward Alzheimer's disease. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring11, pp.98-107.

Evangelos Chatzaroulas, Vytenis Sliogeris, Pedro Victori, Francesca M. Buffa, Sotiris Moschoyiannis, Roman Bauer (2022)A Structural Characterisation of the Mitogen-Activated Protein Kinase Network in Cancer, In: Symmetry (Basel)14(5)1009 Mdpi

Gene regulatory networks represent collections of regulators that interact with each other and with other molecules to govern gene expression. Biological signalling networks model how signals are transmitted and how activities are coordinated in the cell. The study of the structure of such networks in complex diseases such as cancer can provide insights into how they function, and consequently, suggest suitable treatment approaches. Here, we explored such topological characteristics in the example of a mitogen-activated protein kinase (MAPK) signalling network derived from published studies in cancer. We employed well-established techniques to conduct network analyses, and collected information on gene function as obtained from large-scale public databases. This allowed us to map topological and functional relationships, and build hypotheses on this network's functional consequences. In particular, we find that the topology of this MAPK network is highly non-random, modular and robust. Moreover, analysis of the network's structure indicates the presence of organisational features of cancer hallmarks, expressed in an asymmetrical manner across communities of the network. Finally, our results indicate that the organisation of this network renders it problematic to use treatment approaches that focus on a single target. Our analysis suggests that multi-target attacks in a well-orchestrated manner are required to alter how the network functions. Overall, we propose that complex network analyses combined with pharmacological insights will help inform on future treatment strategies, exploiting structural vulnerabilities of signalling and regulatory networks in cancer.

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