The Rubiaceae tribe Rubieae has a world-wide distribution with up to 1,000 species. These collectively exhibit an enormous ecological and morphological diversity, making Rubieae an excellent group ...for macro- and microevolutionary studies. Previous molecular phylogenetic analyses used only a limited sampling within the tribe or missed lineages crucial for understanding character evolution in this group. Here, we analyze sequences from two plastid spacer regions as well as morphological and biogeographic data from an extensive and evenly distributed sampling to establish a sound phylogenetic framework. This framework serves as a basis for our investigation of the evolution of important morphological characters and the biogeographic history of the Rubieae. The tribe includes three major clades, the Kelloggiinae Clade (Kelloggia), the Rubiinae Clade (Didymaea, Rubia) and the most species-rich Galiinae Clade (Asperula, Callipeltis, Crucianella, Cruciata, Galium, Mericarpaea, Phuopsis, Sherardia, Valantia). Within the Galiinae Clade, the largest genera Galium and Asperula are para- and polyphyletic, respectively. Smaller clades, however, usually correspond to currently recognized taxa (small genera or sections within genera), which may be used as starting points for a refined classification in this clade. Life-form (perennial versus annual), flower shape (long versus short corolla tube) and fruit characters (dry versus fleshy, with or without uncinate hairs) are highly homoplasious and have changed multiple times independently. Inference on the evolution of leaf whorls, a characteristic feature of the tribe, is sensitive to model choice. Multi-parted leaf whorls appear to have originated from opposite leaves with two small interpetiolar stipules that are subsequently enlarged and increased in number. Early diversification of Rubieae probably started during the Miocene in western Eurasia. Disjunctions between the Old and the New World possibly are due to connections via a North Atlantic land bridge. Diversification of the Galiineae Clade started later in the Miocene, probably in the Mediterranean, from where lineages reached, often multiple times, Africa, eastern Asia and further on the Americas and Australia.
microRNAs (miRNAs) regulate gene expression at post-transcriptional level by repressing target RNA molecules. Competition to bind miRNAs tends in turn to correlate their targets, establishing ...effective RNA-RNA interactions that can influence expression levels, buffer fluctuations and promote signal propagation. Such a potential has been characterized mathematically for small motifs both at steady state and away from stationarity. Experimental evidence, on the other hand, suggests that competing endogenous RNA (ceRNA) crosstalk is rather weak. Extended miRNA-RNA networks could however favour the integration of many crosstalk interactions, leading to significant large-scale effects in spite of the weakness of individual links. To clarify the extent to which crosstalk is sustained by the miRNA interactome, we have studied its emergent systemic features in silico in large-scale miRNA-RNA network reconstructions. We show that, although generically weak, system-level crosstalk patterns (i) are enhanced by transcriptional heterogeneities, (ii) can achieve high-intensity even for RNAs that are not co-regulated, (iii) are robust to variability in transcription rates, and (iv) are significantly non-local, i.e. correlate weakly with miRNA-RNA interaction parameters. Furthermore, RNA levels are generically more stable when crosstalk is strongest. As some of these features appear to be encoded in the network's topology, crosstalk may functionally be favoured by natural selection. These results suggest that, besides their repressive role, miRNAs mediate a weak but resilient and context-independent network of cross-regulatory interactions that interconnect the transcriptome, stabilize expression levels and support system-level responses.
From how to define a species to the folly of faulty applications of cladistics to connections between conservation and evolutionary biology, On Evolution takes the reader on a personal journey into ...the mind of one of the world's leading evolutionists.
Multidomain network classification has attracted significant attention in data integration and machine learning, which can enhance network classification or prediction performance by integrating ...information from different sources. Despite the previous success, existing multidomain network learning methods usually assume that different views are available for the same set of instances, and thus, they seek a consistent classification result for all domains. However, in many real-world problems, each domain has its specific instance set, and one instance in one domain may correspond to multiple instances in another domain. Moreover, due to the rapid growth of data sources, different domains may not be relevant to each other, which asks for selecting domains relevant to the target/focused domain. A key challenge under this setting is how to achieve accurate prediction by integrating different data representations without losing data information. In this paper, we propose a semisupervised classification approach for a multidomain network based on label propagation, i.e., multidomain classification with domain selection (MCS), which can deal with the cross-domain information and different instance sets in domains. In particular, with sparse weight properties, the proposed MCS can automatically identify those domains relevant to our target domain by assigning them higher weights than the other irrelevant domains. This not only significantly improves a classification accuracy but also helps to obtain optimal network partition for the target domain. From the theoretical viewpoint, we equivalently decompose MCS into two simpler subproblems with analytical solutions, which can be efficiently solved by their computational procedures. Extensive experimental results on both synthetic and real-world data sets empirically demonstrate the advantages of the proposed approach in terms of both prediction performance and domain selection ability.
Monitoring the networked dynamics via the subset of nodes is essential for a variety of scientific and operational purposes. When there is a lack of an explicit model and networked signal space, ...traditional observability analysis and non-convex methods are insufficient. Current data-driven Koopman linearization, although derives a linear evolution model for selected vector-valued observable of original state-space, may result in a large sampling set due to: (i) the large size of polynomial based observables (<inline-formula><tex-math notation="LaTeX">O(N^2)</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">N</tex-math></inline-formula> number of nodes in network), and (ii) not factoring in the nonlinear dependency betweenobservables. In this work, to achieve linear scaling (<inline-formula><tex-math notation="LaTeX">O(N)</tex-math></inline-formula>) and a small set of sampling nodes, wepropose to combine a novel Log-Koopman operator and nonlinear Graph Fourier Transform (NL-GFT) scheme. First, the Log-Koopman operator is able to reduce the size of observables by transforming multiplicative poly-observable to logarithm summation. Second, anonlinear GFT concept and sampling theory are provided to exploit the nonlinear dependence of observables for observability analysis using Koopman evolution model. The results demonstrate that the proposed Log-Koopman NL-GFT scheme can (i) linearize unknownnonlinear dynamics using <inline-formula><tex-math notation="LaTeX">O(N)</tex-math></inline-formula> observables, and (ii) achieve lower number of sampling nodes, compared with the state-of-the art polynomial Koopman based observability analysis.
Natural Evolution Strategies Wierstra, D.; Schaul, T.; Peters, J. ...
2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence),
2008-June
Conference Proceeding
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This paper presents natural evolution strategies (NES), a novel algorithm for performing real-valued dasiablack boxpsila function optimization: optimizing an unknown objective function where ...algorithm-selected function measurements constitute the only information accessible to the method. Natural evolution strategies search the fitness landscape using a multivariate normal distribution with a self-adapting mutation matrix to generate correlated mutations in promising regions. NES shares this property with covariance matrix adaption (CMA), an evolution strategy (ES) which has been shown to perform well on a variety of high-precision optimization tasks. The natural evolution strategies algorithm, however, is simpler, less ad-hoc and more principled. Self-adaptation of the mutation matrix is derived using a Monte Carlo estimate of the natural gradient towards better expected fitness. By following the natural gradient instead of the dasiavanillapsila gradient, we can ensure efficient update steps while preventing early convergence due to overly greedy updates, resulting in reduced sensitivity to local suboptima. We show NES has competitive performance with CMA on unimodal tasks, while outperforming it on several multimodal tasks that are rich in deceptive local optima.
The arrival in Sydney of a copy of the first edition of The Origin of Species early in March 1860, purchased and annotated in pencil by a botanically aspiring colonist, William Woolls, yielded a ...significant insight into the reception of Darwin's theory of evolution at a remote outpost of the scientific world. A Christian "creationist," Woolls, rejected the theory, and his pencilled objections and questioning marked an attitude that would predominate among Australian naturalists for almost four decades. British institutional approaches coloured the development of colonial science. The personal and research influence of the great British palaeontologist, Sir Richard Owen, and his concept of a "final cause" held prevailing sway, and it was not until the mid to late 1880s that a new breed of trained pro-Darwinian scientists from the United Kingdom percolated the teaching posts in the three Australian universities and promoted a paradigm shift in Australian biological science. Darwin's long consideration of the platypus (first sighted in 1836 on his visit to the Cox's River, New South Wales) as a key aberrant species in the evolutionary chain, finds relevance in this re-evaluation. Evolutionary ideas won widening acceptance at the Royal Society of New South Wales following the creation and award of the Clarke Medal in the late '80s as the first scientific award in Australia.
This letter investigates an emergent synchronization property within a set of non-competing multi-agent systems. The primary objective is to develop behavioral mathematical models that enable ...multiple groups of agents to adhere to predetermined paths while concurrently achieving consensus among corresponding members within each group. In this pursuit, the inherent coordination challenge is addressed while acknowledging absence of communication channels between the different agent groups but requiring a centralized and omniscient authority that assigns suitable and prescribed reference curves to track for each swarm. As a further assumption, the described emergent synchronization property is achieved by exploiting a complete communication graph, with an all-to-all communication topology in each multi-agent system. The proposed solution exploits a diffeomorphic mapping to translate the task into two independent and simpler problems: the first one relates to reaching the curve of interest and the second to moving on it while maintaining the synchronization condition between couple of agents.
The evolution of opsin genes is of great interest because it can provide insight into the evolution of light detection and vision. An interesting group in which to study opsins is Cnidaria because it ...is a basal phylum sister to Bilateria with much visual diversity within the phylum. Hydra vulgaris (H. vulgaris) is a cnidarian with a plethora of genomic resources to characterize the opsin gene family. This eyeless cnidarian has a behavioral reaction to light, but it remains unknown which of its many opsins functions in light detection. Here, we used phylogenetics and RNA-seq to investigate the molecular evolution of opsin genes and their expression in H. vulgaris. We explored where opsin genes are located relative to each other in an improved genome assembly and where they belong in a cnidarian opsin phylogenetic tree. In addition, we used RNA-seq data from different tissues of the H. vulgaris adult body and different time points during regeneration and budding stages to gain insight into their potential functions.
We identified 45 opsin genes in H. vulgaris, many of which were located near each other suggesting evolution by tandem duplications. Our phylogenetic tree of cnidarian opsin genes supported previous claims that they are evolving by lineage-specific duplications. We identified two H. vulgaris genes (HvOpA1 and HvOpB1) that fall outside of the two commonly determined Hydra groups; these genes possibly have a function in nematocytes and mucous gland cells respectively. We also found opsin genes that have similar expression patterns to phototransduction genes in H. vulgaris. We propose a H. vulgaris phototransduction cascade that has components of both ciliary and rhabdomeric cascades.
This extensive study provides an in-depth look at the molecular evolution and expression of H. vulgaris opsin genes. The expression data that we have quantified can be used as a springboard for additional studies looking into the specific function of opsin genes in this species. Our phylogeny and expression data are valuable to investigations of opsin gene evolution and cnidarian biology.
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