@misc{StoetzelApriRoeblitz2014, author = {St{\"o}tzel, Claudia and Apri, Mochamad and R{\"o}blitz, Susanna}, title = {A reduced ODE model of the bovine estrous cycle}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-51594}, year = {2014}, abstract = {This work deals with the reduction of a previously developed ODE model for the bovine estrous cycle. After applying a method for exploring the parameter space by Apri et al. (2012), we perform structure-based reduction steps and several system specific adaptations. Overall, the original model consisting of 15 ODEs and 60 parameters is reduced to a model of 10 odes and 38 parameters. The reduced model qualitatively reproduces the state trajectories of the original model.}, language = {en} } @inproceedings{ManciniSalvoMarietal.2014, author = {Mancini, Toni and Salvo, Ivano and Mari, Federico and Melatti, Igor and Massini, Annalisa and Sinisi, Stefano and Tronci, Enrico and Davi, Francesco and Dierkes, Thomas and Ehrig, Rainald and R{\"o}blitz, Susanna and Leeners, Brigitte and Kr{\"u}ger, Tillmann H. C. and Egli, Marcel and Ille, Fabian}, title = {Patient-Specific Models from Inter-Patient Biological Models and Clinical Records}, booktitle = {Proceedings of the 14th Conference on Formal Methods in Computer-Aided Design (FMCAD 2014)}, pages = {207 -- 214}, year = {2014}, language = {en} } @article{StoetzelEhrigBoeretal.2014, author = {St{\"o}tzel, Claudia and Ehrig, Rainald and Boer, H. Marike T. and Pl{\"o}ntzke, Julia and R{\"o}blitz, Susanna}, title = {Exploration of different wave patterns in a model of the bovine estrous cycle by Fourier analysis}, journal = {BIOMAT - Proceedings of the 14th International Symposium on Mathematical and Computational Biology, Bedlewo, Poland}, year = {2014}, abstract = {Cows typically have different numbers of follicular waves during their hormonal cycle. Understanding the underlying regulations leads to insights into the reasons for declined fertility, a phenomenon that has been observed during the last decades. We present a systematic approach based on Fourier analysis to examine how parameter changes in a model of the bovine estrous cycle lead to different wave patterns. Even without any biological considerations, this allows to detect the responsible model parameters that control the type of periodicity of the solution, thus supporting experimental planning of animal scientists.}, language = {en} } @article{HengartnerKruegerGeraedtsetal.2017, author = {Hengartner, Michael and Kr{\"u}ger, Tillmann H. C. and Geraedts, Kirsten and Tronci, Enrico and Mancini, Toni and Ille, Fabian and Egli, Marcel and R{\"o}blitz, Susanna and Ehrig, Rainald and Saleh, Lanja and Spanaus, Katharina and Schippert, Cordula and Zhang, Yuanyuan and Leeners, Brigitte}, title = {Negative affect is unrelated to fluctuations in hormone levels across the menstrual cycle: evidence from a multisite observational study across two successive cycles}, volume = {99}, journal = {Journal of Psychosomatic Research}, doi = {10.1016/j.jpsychores.2017.05.018}, pages = {21 -- 27}, year = {2017}, language = {en} } @misc{LangeSchwiegerPloentzkeetal.2017, author = {Lange, Alexander and Schwieger, Robert and Pl{\"o}ntzke, Julia and Sch{\"a}fer, Stefan and R{\"o}blitz, Susanna}, title = {Follicular competition: the selection of dominant follicles as a synergistic effect}, issn = {1438-0064}, doi = {https://doi.org/10.1007/s00285-018-1284-0}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-63863}, year = {2017}, abstract = {The estrous cycle of mono-ovulatory species such as cows or humans, is known to show two or more waves of follicular growth and decline between two successive ovulations. Within each wave, there is one dominant follicle escorted by subordinate follicles of varying number. Under the surge of the luteinizing hormone a growing dominant follicle ovulates. Rarely the number of ovulating follicles exceeds one. In the biological literature, the change of hormonal concentrations and individually varying numbers of follicular receptors are made responsible for the selection of exactly one dominant follicle, yet a clear cause has not been identified. In this paper, we suggest a synergistic explanation based on competition, formulated by a parsimoniously defined system of ordinary differential equations (ODEs) that quantifies the time evolution of multiple follicles and their competitive interaction during one wave. Not discriminating between follicles, growth and decline are given by fixed rates. Competition is introduced via a growth-suppressing term, equally supported by all follicles. We prove that the number of dominant follicles is determined exclusively by the ratio of follicular growth and competition. This number turns out to be independent of the number of subordinate follicles. The asymptotic behavior of the corresponding dynamical system is investigated rigorously, where we demonstrate that the omega-limit set only contains fixed points. When also including follicular decline, our ODEs perfectly resemble ultrasound data of bovine follicles. Implications for the involved but not explicitly modeled hormones are discussed.}, language = {en} } @article{LeenersKruegerGeraedtsetal.2017, author = {Leeners, Brigitte and Kr{\"u}ger, Tillmann H. C. and Geraedts, Kirsten and Tronci, Enrico and Mancini, Toni and Ille, Fabian and Egli, Marcel and R{\"o}blitz, Susanna and Saleh, Lanja and Spanhaus, K. and Schippert, Cordula and Zhang, Y. and Hengartner, M. P.}, title = {Lack of association between female hormone levels and visuospatial working memory, divided attention and cognitive bias across two consecutive menstrual cycles}, journal = {Front. Behav. Neurosci.}, doi = {10.3389/fnbeh.2017.00120}, year = {2017}, language = {en} } @misc{BockmayrSiebertRoeblitzetal.2014, author = {Bockmayr, Alexander and Siebert, Heike and R{\"o}blitz, Susanna and Sch{\"u}tte, Christof and Deuflhard, Peter}, title = {Advanced mathematical modeling in systems biology}, volume = {1}, journal = {MATHEON-Mathematics for Key Technologies}, editor = {Deuflhard, Peter and Gr{\"o}tschel, Martin and H{\"o}mberg, Dietmar and Kramer, J{\"u}rg and Mehrmann, Volker and Polthier, Konrad and Schmidt, Frank and Sch{\"u}tte, Christof and Skutela, Martin and Sprekels, J{\"u}rgen}, publisher = {European Mathematical Society}, pages = {29 -- 44}, year = {2014}, language = {en} } @misc{KlebanovSikorskiSchuetteetal.2016, author = {Klebanov, Ilja and Sikorski, Alexander and Sch{\"u}tte, Christof and R{\"o}blitz, Susanna}, title = {Prior estimation and Bayesian inference from large cohort data sets}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-57475}, year = {2016}, abstract = {One of the main goals of mathematical modelling in systems biology related to medical applications is to obtain patient-specific parameterisations and model predictions. In clinical practice, however, the number of available measurements for single patients is usually limited due to time and cost restrictions. This hampers the process of making patient-specific predictions about the outcome of a treatment. On the other hand, data are often available for many patients, in particular if extensive clinical studies have been performed. Using these population data, we propose an iterative algorithm for contructing an informative prior distribution, which then serves as the basis for computing patient-specific posteriors and obtaining individual predictions. We demonsrate the performance of our method by applying it to a low-dimensional parameter estimation problem in a toy model as well as to a high-dimensional ODE model of the human menstrual cycle, which represents a typical example from systems biology modelling.}, language = {en} } @article{KryvenRoeblitzSchuette2015, author = {Kryven, Ivan and R{\"o}blitz, Susanna and Sch{\"u}tte, Christof}, title = {Solution of the chemical master equation by radial basis functions approximation with interface tracking}, volume = {9}, journal = {BMC Systems Biology}, number = {67}, doi = {10.1186/s12918-015-0210-y}, pages = {1 -- 12}, year = {2015}, abstract = {Background. The chemical master equation is the fundamental equation of stochastic chemical kinetics. This differential-difference equation describes temporal evolution of the probability density function for states of a chemical system. A state of the system, usually encoded as a vector, represents the number of entities or copy numbers of interacting species, which are changing according to a list of possible reactions. It is often the case, especially when the state vector is high-dimensional, that the number of possible states the system may occupy is too large to be handled computationally. One way to get around this problem is to consider only those states that are associated with probabilities that are greater than a certain threshold level. Results. We introduce an algorithm that significantly reduces computational resources and is especially powerful when dealing with multi-modal distributions. The algorithm is built according to two key principles. Firstly, when performing time integration, the algorithm keeps track of the subset of states with significant probabilities (essential support). Secondly, the probability distribution that solves the equation is parametrised with a small number of coefficients using collocation on Gaussian radial basis functions. The system of basis functions is chosen in such a way that the solution is approximated only on the essential support instead of the whole state space. Discussion. In order to demonstrate the effectiveness of the method, we consider four application examples: a) the self-regulating gene model, b) the 2-dimensional bistable toggle switch, c) a generalisation of the bistable switch to a 3-dimensional tristable problem, and d) a 3-dimensional cell differentiation model that, depending on parameter values, may operate in bistable or tristable modes. In all multidimensional examples the manifold containing the system states with significant probabilities undergoes drastic transformations over time. This fact makes the examples especially challenging for numerical methods. Conclusions. The proposed method is a new numerical approach permitting to approximately solve a wide range of problems that have been hard to tackle until now. A full representation of multi-dimensional distributions is recovered. The method is especially attractive when dealing with models that yield solutions of a complex structure, for instance, featuring multi-stability. Electronic version: http://www.biomedcentral.com/1752-0509/9/67}, language = {en} } @misc{EhrigDierkesSchaeferetal.2016, author = {Ehrig, Rainald and Dierkes, Thomas and Sch{\"a}fer, Stefan and R{\"o}blitz, Susanna and Tronci, Enrico and Mancini, Toni and Salvo, Ivano and Alimguzhin, Vadim and Mari, Federico and Melatti, Igor and Massini, Annalisa and Kr{\"u}ger, Tillmann H. C. and Egli, Marcel and Ille, Fabian and Leeners, Brigitte}, title = {An Integrative Approach for Model Driven Computation of Treatments in Reproductive Medicine}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-57103}, year = {2016}, abstract = {We present an overview of the current status of the European collaborative project PAEON. The challenge of PAEON is to provide specialists in reproduc- tive medicine with a computerised model of the menstrual cycle under normal and various pathological conditions, which will allow them to get further in- sight in fertility dynamics. This model also enables the simulation of treatment protocols, which were used within in vitro fertilization. By the definition of virtual patients through biologically admissible parametrizations our approach allows not only the evaluation of a given treatment strategy in silico, but also the design and optimization of such protocols. Once a protocol is formalized in the virtual hospital, the success can be controlled by a treatment execution monitor, which works then as a clinical decision support system. All these tools will be combined in a virtual hospital environment, enabling the access to the PAEON services through the web.}, language = {en} }