Edge Label Placement in Layered Graph Drawing

Many visual languages based on node-link diagrams use edge labels. We describe different strategies of placing edge labels in the context of the layered approach to graph drawing and investigate ways of encoding edge direction in labels. We evaluate the label placement strategies based on both common aesthetic criteria and a controlled experiment. We find that placing labels on their edge can lead to more compact diagrams. Also, placing labels with additional arrows indicating edge direction can help users navigate in large diagrams and is generally preferred by participants of our experiment, outperforming other ways of indicating edge direction

Lung epithelial stem cells and their niches : Fgf10 takes center stage

Throughout life adult animals crucially depend on stem cell populations to maintain and repair their tissues to ensure life-long organ function. Stem cells are characterized by their capacity to extensively self-renew and give rise to one or more differentiated cell types. These powerful stem cell properties are key to meet the changing demand for tissue replacement during normal lung homeostasis and regeneration after lung injury. Great strides have been made over the last few years to identify and characterize lung epithelial stem cells as well as their lineage relationships. Unfortunately, knowledge on what regulates the behavior and fate specification of lung epithelial stem cells is still limited, but involves communication with their microenvironment or niche, a local tissue environment that hosts and influences the behaviors or characteristics of stem cells and that comprises other cell types and extracellular matrix. As such, an intimate and dynamic epithelial-mesenchymal cross-talk, which is also essential during lung development, is required for normal homeostasis and to mount an appropriate regenerative response after lung injury. Fibroblast growth factor 10 (Fgf10) signaling in particular seems to be a well-conserved signaling pathway governing epithelial-mesenchymal interactions during lung development as well as between different adult lung epithelial stem cells and their niches. On the other hand, disruption of these reciprocal interactions leads to a dysfunctional epithelial stem cell-niche unit, which may culminate in chronic lung diseases such as chronic obstructive pulmonary disease (COPD), chronic asthma and idiopathic pulmonary fibrosis (IPF)

Phylogenetic comparative assembly

Husemann P, Stoye J. Phylogenetic Comparative Assembly. Algorithms for Molecular Biology. 2010;5(1): 3.BACKGROUND:Recent high throughput sequencing technologies are capable of generating a huge amount of data for bacterial genome sequencing projects. Although current sequence assemblers successfully merge the overlapping reads, often several contigs remain which cannot be assembled any further. It is still costly and time consuming to close all the gaps in order to acquire the whole genomic sequence. RESULTS:Here we propose an algorithm that takes several related genomes and their phylogenetic relationships into account to create a graph that contains the likelihood for each pair of contigs to be adjacent. Subsequently, this graph can be used to compute a layout graph that shows the most promising contig adjacencies in order to aid biologists in finishing the complete genomic sequence. The layout graph shows unique contig orderings where possible, and the best alternatives where necessary. CONCLUSIONS:Our new algorithm for contig ordering uses sequence similarity as well as phylogenetic information to estimate adjacencies of contigs. An evaluation of our implementation shows that it performs better than recent approaches while being much faster at the same tim

Problematic internet use: a general perspective

How the Internet is used and any negative outcomes of engagement with it—especially with regards to children—is a topic of great interest, bearing legitimate investigation. Proposed identifiers of problematic internet use(PIU) include aspects of use in correlation with distress or impairment across biological, psychological, sociological, and/or occupational/academic functioning. Adolescents and those with vulnerabilities across developmental or sociological domains are particularly susceptible. Although validated instruments have been utilized to assess PIU, concerns surrounding the methodology, currency, and some validation measures of existing and cross-sectional screening tools and a lack of those with true external validity and variance, combined with some disagreement surrounding PIU, have impeded its diagnostic acceptance. Current investigative approaches to PIU include clarifying problematic gambling and gaming criteria, psychotherapeutic therapy, pharmacological interventions, and non-invasive neurostimulation therapies targeting cortical brain regions. As child screen time appears to be increasing, further research, ethical health/social policy changes, and digital literacy programs are strongly endorsed. To avoid online engagement dysregulating or harming children, digital policy youth user protection standards, pragmatic key player dialogues, transparent reassessments of digital-centric business models without compromising less resourced countries, and even globally agreed child online safety regulations are also recommended

Metabolome Based Reaction Graphs of M. tuberculosis and M. leprae: A Comparative Network Analysis

BACKGROUND: Several types of networks, such as transcriptional, metabolic or protein-protein interaction networks of various organisms have been constructed, that have provided a variety of insights into metabolism and regulation. Here, we seek to exploit the reaction-based networks of three organisms for comparative genomics. We use concepts from spectral graph theory to systematically determine how differences in basic metabolism of organisms are reflected at the systems level and in the overall topological structures of their metabolic networks. METHODOLOGY/PRINCIPAL FINDINGS: Metabolome-based reaction networks of Mycobacterium tuberculosis, Mycobacterium leprae and Escherichia coli have been constructed based on the KEGG LIGAND database, followed by graph spectral analysis of the network to identify hubs as well as the sub-clustering of reactions. The shortest and alternate paths in the reaction networks have also been examined. Sub-cluster profiling demonstrates that reactions of the mycolic acid pathway in mycobacteria form a tightly connected sub-cluster. Identification of hubs reveals reactions involving glutamate to be central to mycobacterial metabolism, and pyruvate to be at the centre of the E. coli metabolome. The analysis of shortest paths between reactions has revealed several paths that are shorter than well established pathways. CONCLUSIONS: We conclude that severe downsizing of the leprae genome has not significantly altered the global structure of its reaction network but has reduced the total number of alternate paths between its reactions while keeping the shortest paths between them intact. The hubs in the mycobacterial networks that are absent in the human metabolome can be explored as potential drug targets. This work demonstrates the usefulness of constructing metabolome based networks of organisms and the feasibility of their analyses through graph spectral methods. The insights obtained from such studies provide a broad overview of the similarities and differences between organisms, taking comparative genomics studies to a higher dimension

Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals

A Scalable Approach for Discovering Conserved Active Subnetworks across Species

Overlaying differential changes in gene expression on protein interaction networks has proven to be a useful approach to interpreting the cell's dynamic response to a changing environment. Despite successes in finding active subnetworks in the context of a single species, the idea of overlaying lists of differentially expressed genes on networks has not yet been extended to support the analysis of multiple species' interaction networks. To address this problem, we designed a scalable, cross-species network search algorithm, neXus (Network - cross(X)-species - Search), that discovers conserved, active subnetworks based on parallel differential expression studies in multiple species. Our approach leverages functional linkage networks, which provide more comprehensive coverage of functional relationships than physical interaction networks by combining heterogeneous types of genomic data. We applied our cross-species approach to identify conserved modules that are differentially active in stem cells relative to differentiated cells based on parallel gene expression studies and functional linkage networks from mouse and human. We find hundreds of conserved active subnetworks enriched for stem cell-associated functions such as cell cycle, DNA repair, and chromatin modification processes. Using a variation of this approach, we also find a number of species-specific networks, which likely reflect mechanisms of stem cell function that have diverged between mouse and human. We assess the statistical significance of the subnetworks by comparing them with subnetworks discovered on random permutations of the differential expression data. We also describe several case examples that illustrate the utility of comparative analysis of active subnetworks