@article{VincentKenfackSenthilkumaretal.2010, author = {Vincent, Uchechukwu E. and Kenfack, Anatole and Senthilkumar, Dharmapuri Vijayan and Mayer, Dieter and Kurths, J{\"u}rgen}, title = {Current reversals and synchronization in coupled ratchets}, issn = {1539-3755}, doi = {10.1103/Physreve.82.046208}, year = {2010}, abstract = {Current reversal is an intriguing phenomenon that has been central to recent experimental and theoretical investigations of transport based on ratchet mechanism. By considering a system of two interacting ratchets, we demonstrate how the coupling can be used to control the reversals. In particular, we find that current reversal that exists in a single driven ratchet system can ultimately be eliminated with the presence of a second ratchet. For specific coupling strengths a current-reversal free regime has been detected. Furthermore, in the fully synchronized state characterized by the coupling threshold k(th), a specific driving amplitude a(opt) is found for which the transport is optimum.}, language = {en} } @article{HempelKoseskaKurthsetal.2011, author = {Hempel, Stefan and Koseska, Aneta and Kurths, J{\"u}rgen and Nikoloski, Zoran}, title = {Inner composition alignment for inferring directed networks from short time series}, series = {Physical review letters}, volume = {107}, journal = {Physical review letters}, number = {5}, publisher = {American Physical Society}, address = {College Park}, issn = {0031-9007}, doi = {10.1103/PhysRevLett.107.054101}, pages = {4}, year = {2011}, abstract = {Identifying causal links (couplings) is a fundamental problem that facilitates the understanding of emerging structures in complex networks. We propose and analyze inner composition alignment-a novel, permutation-based asymmetric association measure to detect regulatory links from very short time series, currently applied to gene expression. The measure can be used to infer the direction of couplings, detect indirect (superfluous) links, and account for autoregulation. Applications to the gene regulatory network of E. coli are presented.}, language = {en} } @article{HempelKoseskaNikoloskietal.2011, author = {Hempel, Sabrina and Koseska, Aneta and Nikoloski, Zoran and Kurths, J{\"u}rgen}, title = {Unraveling gene regulatory networks from time-resolved gene expression data - a measures comparison study}, series = {BMC bioinformatics}, volume = {12}, journal = {BMC bioinformatics}, number = {1}, publisher = {BioMed Central}, address = {London}, issn = {1471-2105}, doi = {10.1186/1471-2105-12-292}, pages = {26}, year = {2011}, abstract = {Background: Inferring regulatory interactions between genes from transcriptomics time-resolved data, yielding reverse engineered gene regulatory networks, is of paramount importance to systems biology and bioinformatics studies. Accurate methods to address this problem can ultimately provide a deeper insight into the complexity, behavior, and functions of the underlying biological systems. However, the large number of interacting genes coupled with short and often noisy time-resolved read-outs of the system renders the reverse engineering a challenging task. Therefore, the development and assessment of methods which are computationally efficient, robust against noise, applicable to short time series data, and preferably capable of reconstructing the directionality of the regulatory interactions remains a pressing research problem with valuable applications. Results: Here we perform the largest systematic analysis of a set of similarity measures and scoring schemes within the scope of the relevance network approach which are commonly used for gene regulatory network reconstruction from time series data. In addition, we define and analyze several novel measures and schemes which are particularly suitable for short transcriptomics time series. We also compare the considered 21 measures and 6 scoring schemes according to their ability to correctly reconstruct such networks from short time series data by calculating summary statistics based on the corresponding specificity and sensitivity. Our results demonstrate that rank and symbol based measures have the highest performance in inferring regulatory interactions. In addition, the proposed scoring scheme by asymmetric weighting has shown to be valuable in reducing the number of false positive interactions. On the other hand, Granger causality as well as information-theoretic measures, frequently used in inference of regulatory networks, show low performance on the short time series analyzed in this study. Conclusions: Our study is intended to serve as a guide for choosing a particular combination of similarity measures and scoring schemes suitable for reconstruction of gene regulatory networks from short time series data. We show that further improvement of algorithms for reverse engineering can be obtained if one considers measures that are rooted in the study of symbolic dynamics or ranks, in contrast to the application of common similarity measures which do not consider the temporal character of the employed data. Moreover, we establish that the asymmetric weighting scoring scheme together with symbol based measures (for low noise level) and rank based measures (for high noise level) are the most suitable choices.}, language = {en} } @article{GrimbsArnoldKoseskaetal.2011, author = {Grimbs, Sergio and Arnold, Anne and Koseska, Aneta and Kurths, J{\"u}rgen and Selbig, Joachim and Nikoloski, Zoran}, title = {Spatiotemporal dynamics of the Calvin cycle multistationarity and symmetry breaking instabilities}, series = {Biosystems : journal of biological and information processing sciences}, volume = {103}, journal = {Biosystems : journal of biological and information processing sciences}, number = {2}, publisher = {Elsevier}, address = {Oxford}, issn = {0303-2647}, doi = {10.1016/j.biosystems.2010.10.015}, pages = {212 -- 223}, year = {2011}, abstract = {The possibility of controlling the Calvin cycle has paramount implications for increasing the production of biomass. Multistationarity, as a dynamical feature of systems, is the first obvious candidate whose control could find biotechnological applications. Here we set out to resolve the debate on the multistationarity of the Calvin cycle. Unlike the existing simulation-based studies, our approach is based on a sound mathematical framework, chemical reaction network theory and algebraic geometry, which results in provable results for the investigated model of the Calvin cycle in which we embed a hierarchy of realistic kinetic laws. Our theoretical findings demonstrate that there is a possibility for multistationarity resulting from two sources, homogeneous and inhomogeneous instabilities, which partially settle the debate on multistability of the Calvin cycle. In addition, our tractable analytical treatment of the bifurcation parameters can be employed in the design of validation experiments.}, language = {en} }