2010, Sun, Xiaoliang, Zou, Yong, Nikiforova, Victoria, Kurths, Jürgen, Walther, Dirk

Background: High complexity is considered a hallmark of living systems. Here we investigate the complexity of temporal gene expression patterns using the concept of Permutation Entropy (PE) first introduced in dynamical systems theory. The analysis of gene expression data has so far focused primarily on the identification of differentially expressed genes, or on the elucidation of pathway and regulatory relationships. We aim to study gene expression time series data from the viewpoint of complexity.Results: Applying the PE complexity metric to abiotic stress response time series data in Arabidopsis thaliana, genes involved in stress response and signaling were found to be associated with the highest complexity not only under stress, but surprisingly, also under reference, non-stress conditions. Genes with house-keeping functions exhibited lower PE complexity. Compared to reference conditions, the PE of temporal gene expression patterns generally increased upon stress exposure. High-complexity genes were found to have longer upstream intergenic regions and more cis-regulatory motifs in their promoter regions indicative of a more complex regulatory apparatus needed to orchestrate their expression, and to be associated with higher correlation network connectivity degree. Arabidopsis genes also present in other plant species were observed to exhibit decreased PE complexity compared to Arabidopsis specific genes.Conclusions: We show that Permutation Entropy is a simple yet robust and powerful approach to identify temporal gene expression profiles of varying complexity that is equally applicable to other types of molecular profile data.

2016, Wu, Wenming, Guijt, Rosanne M., Silina, Yuliya E., Koch, Marcus, Manz, Andreas

We report a simple fast, practical and effective method for the replication of the complex venation patterns of natural leaves into PDMS with accuracy down to a lateral size of 500 nm. Optimising the amount of crosslinker enabled the replication and sealing of the microvascular structures to yield enclosed microfluidic networks. The use of plant leaves as templates for soft lithography was demonstrated across over ten species and included reticulate, arcuate, pinnate, parallel and palmate venation patterns. SEM imaging revealed replication of the plants microscopic and sub-microscopic topography into the PDMS structures, making this method especially attractive for mimicking biological structures for in vitro assays. Flow analysis revealed that the autonomous liquid transport velocity in 1st-order microchannel was 1.5–2.2 times faster than that in the 2nd-order microchannels across three leaf types, with the sorptivity rule surprisingly preserved during self-powered flow through leaf-inspired vascularity from Carpinus betulus.