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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.
Glacial advances constrained by Be-10 exposure dating of bedrock landslides, Kyrgyz Tien Shan
(2011)
Numerous large landslide deposits occur in the Tien Shan, a tectonically active intraplate orogen in Central Asia. Yet their significance in Quaternary landscape evolution and natural hazard assessment remains unresolved due to the lack of "absolute" age constraints. Here we present the first Be-10 exposure ages for three prominent (>10(7) m(3)) bedrock landslides that blocked major rivers and formed lakes, two of which subsequently breached, in the northern Kyrgyz Tien Shan. Three Be-10 ages reveal that one landslide in the Alamyedin River occurred at 11-15 ka, which is consistent with two C-14 ages of gastropod shells from reworked loess capping the landslide. One large landslide in Aksu River is among the oldest documented in semi-arid continental interiors, with a Be-10 age of 63-67 ka. The Ukok River landslide deposit(s) yielded variable Be-10 ages, which may result from multiple landslides, and inheritance of Be-10. Two Be-10 ages of 8.2 and 5.9 ka suggest that one major landslide occurred in the early to mid-Holocene, followed by at least one other event between 1.5 and 0.4 ka. Judging from the regional glacial chronology, all three landslides have occurred between major regional glacial advances. Whereas Alamyedin and Ukok can be considered as postglacial in this context, Aksu is of interglacial age. None of the landslide deposits show traces of glacial erosion, hence their locations and I Be ages mark maximum extents and minimum ages of glacial advances, respectively. Using toe-to-headwall altitude ratios of 0.4-0.5, we reconstruct minimum equilibrium-line altitudes that exceed previous estimates by as much as 400 m along the moister northern fringe of the Tien Shan. Our data show that deposits from large landslides can provide valuable spatio-temporal constraints for glacial advances in landscapes where moraines and glacial deposits have low preservation potential. (C) 2011 University of Washington. Published by Elsevier Inc. All rights reserved.
Nonlinear detection of paleoclimate-variability transitions possibly related to human evolution
(2011)
Potential paleoclimatic driving mechanisms acting on human evolution present an open problem of cross-disciplinary scientific interest. The analysis of paleoclimate archives encoding the environmental variability in East Africa during the past 5 Ma has triggered an ongoing debate about possible candidate processes and evolutionary mechanisms. In this work, we apply a nonlinear statistical technique, recurrence network analysis, to three distinct marine records of terrigenous dust flux. Our method enables us to identify three epochs with transitions between qualitatively different types of environmental variability in North and East Africa during the (i) Middle Pliocene (3.35-3.15 Ma B. P.), (ii) Early Pleistocene (2.25-1.6 Ma B. P.), and (iii) Middle Pleistocene (1.1-0.7 Ma B. P.). A deeper examination of these transition periods reveals potential climatic drivers, including (i) large-scale changes in ocean currents due to a spatial shift of the Indonesian throughflow in combination with an intensification of Northern Hemisphere glaciation, (ii) a global reorganization of the atmospheric Walker circulation induced in the tropical Pacific and Indian Ocean, and (iii) shifts in the dominating temporal variability pattern of glacial activity during the Middle Pleistocene, respectively. A reexamination of the available fossil record demonstrates statistically significant coincidences between the detected transition periods and major steps in hominin evolution. This result suggests that the observed shifts between more regular and more erratic environmental variability may have acted as a trigger for rapid change in the development of humankind in Africa.
In this paper, we study the complete synchronization of a class of time-varying delayed coupled chaotic systems using feedback control. In terms of Linear Matrix Inequalities, a sufficient condition is obtained through using a Lyapunov-Krasovskii functional and differential equation in equalities. The conditions can be easily verified and implemented. We present two simulation examples to illustrate the effectiveness of the proposed method.
Synthetic multicellular oscillatory systems controlling protein dynamics with genetic circuits
(2011)
Synthetic biology is a relatively new research discipline that combines standard biology approaches with the constructive nature of engineering. Thus, recent efforts in the field of synthetic biology have given a perspective to consider cells as 'programmable matter'. Here, we address the possibility of using synthetic circuits to control protein dynamics. In particular, we show how intercellular communication and stochasticity can be used to manipulate the dynamical behavior of a population of coupled synthetic units and, in this manner, finely tune the expression of specific proteins of interest, e.g. in large bioreactors.
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.