Nikola S. Müller

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MOTIVATION High-dimensional single-cell snapshot data are becoming widespread in the systems biology community, as a mean to understand biological processes at the cellular level. However, as temporal information is lost with such data, mathematical models have been limited to capture only static features of the underlying cellular mechanisms. RESULTS(More)
How can we automatically spot all outstanding observations in a data set? This question arises in a large variety of applications, e.g. in economy, biology and medicine. Existing approaches to outlier detection suffer from one or more of the following drawbacks: The results of many methods strongly depend on suitable parameter settings being very difficult(More)
Establishment of cell polarity--or symmetry breaking--relies on local accumulation of polarity regulators. Although simple positive feedback is sufficient to drive symmetry breaking, it is highly sensitive to stochastic fluctuations typical for living cells. Here, by integrating mathematical modelling with quantitative experimental validations, we show that(More)
SUMMARY Decreasing costs of modern high-throughput experiments allow for the simultaneous analysis of altered gene activity on various molecular levels. However, these multi-omics approaches lead to a large amount of data, which is hard to interpret for a non-bioinformatician. Here, we present the remotely accessible multilevel ontology analysis (RAMONA).(More)
Glioblastoma is the most aggressive brain tumor in adults with a median survival below 12 months in population-based studies. The main reason for tumor recurrence and progression is constitutive or acquired resistance to the standard of care of surgical resection followed by radiotherapy with concomitant and adjuvant temozolomide (TMZ/RT→TMZ). Here, we(More)
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