How stressed are the banks? An inter-temporal network analysis

Atherosclerosis, a chronic inflammatory disease of the vascular system, presents significant challenges to developing effective molecular diagnostics and novel therapies. A systems biology approach integrating data from large-scale measurements (e.g. transcriptomics, proteomics and genomics) is successfully contributing to deciphering regulatory networks underlying the response of many different cellular systems to perturbations. Such a network analysis strategy using pathway information and data from multiple measurement platforms, tissues and species is a promising approach to elucidate the mechanistic underpinnings of complex diseases. Here, we present our views on the contributions that a systems approach can bring to the study of atherosclerosis, propose ways to tackle the complexity of the disease in a systems manner and review recent systems-level studies of the disease.

As an emerging research approach, social network theory and analysis has been embraced and effectively applied in disciplines that have overlapping interests with sport management researchers including such fields as organizational behavior and sport sociology. Although a number of sport management scholars have investigated network-related concepts, to date no sport management studies have fully utilized the analytical tools that social network theory and analysis have to offer. In conjunction with a discussion about the ontological, epistemological, and methodological perspectives associated with network analysis, this article uses several examples from the sport management and organizational behavior bodies of literature to illustrate a number of the advantageous techniques and insights social network theory and analysis can offer. These examples are meant to provide a general understanding of the utility and applicability of the social network theory and analysis and potentially inspire sport management researchers to adopt a social network lens in their future research endeavors.

Analysis of Network Security Access Space Agency Based Firewall Log In LAPAN Center. Supervisor LIPUR SUGIYANTA, Ph.D and Drs. BACHREN ZAINI, M.Pd. Increased Denial Of Service attacks, and other types of computer network interference, making security an important issue to be considered by all those who take advantage of the presence of the virtual world today. LAPAN Center system along with the information contained within is no exception contained attacks on access computer network security. Such attacks can be prevented at an early stage by analyzing at each access that will go on network security in LAPAN. This research at Analysis of Network Access to know and learn access of network security in firewall log LAPAN Center. This research was conducted with several stages of observation and interviews to employees of LAPAN Center infrastructure. After the stage of observation and interviews, the researchers conducted further data collection and analysis of firewall logs. The study states that the analysis of security access network based firewall log in LAPAN Center in the form of six messages that occur when a network will pass through the firewall. It can be concluded that by doing some analysis phases of network security access based firewall log in LAPAN Center produces a record of every incident inside the firewall logs. The study states that the analysis of security access network based firewall log in LAPAN Center in the form of six messages that occur when a network will pass through the firewall. It can be concluded that by doing some analysis phases of network security access based firewall log in LAPAN Center produces a record of every incident inside the firewall logs. The study states that the analysis of security access network based firewall log in LAPAN Center in the form of six messages that occur when a network will pass through the firewall. It can be concluded that by doing some analysis phases of network security access based firewall log in LAPAN Center produces a record of every incident inside the firewall logs.

Analysis of Network Security Access Space Agency Based Firewall Log In LAPAN Center. Supervisor LIPUR SUGIYANTA, Ph.D and Drs. BACHREN ZAINI, M.Pd. Increased Denial Of Service attacks, and other types of computer network interference, making security an important issue to be considered by all those who take advantage of the presence of the virtual world today. LAPAN Center system along with the information contained within is no exception contained attacks on access computer network security. Such attacks can be prevented at an early stage by analyzing at each access that will go on network security in LAPAN. This research at Analysis of Network Access to know and learn access of network security in firewall log LAPAN Center. This research was conducted with several stages of observation and interviews to employees of LAPAN Center infrastructure. After the stage of observation and interviews, the researchers conducted further data collection and analysis of firewall logs. The study states that the analysis of security access network based firewall log in LAPAN Center in the form of six messages that occur when a network will pass through the firewall. It can be concluded that by doing some analysis phases of network security access based firewall log in LAPAN Center produces a record of every incident inside the firewall logs. The study states that the analysis of security access network based firewall log in LAPAN Center in the form of six messages that occur when a network will pass through the firewall. It can be concluded that by doing some analysis phases of network security access based firewall log in LAPAN Center produces a record of every incident inside the firewall logs. The study states that the analysis of security access network based firewall log in LAPAN Center in the form of six messages that occur when a network will pass through the firewall. It can be concluded that by doing some analysis phases of network security access based firewall log in LAPAN Center produces a record of every incident inside the firewall logs

BackgroundNetwork analyses are often applied to microbial communities using sequencing survey datasets. However, associations in such networks do not necessarily indicate actual biotic interactions, and even if they do, the nature of the interactions commonly remains unclear. While network analyses are valuable for generating hypotheses, the inferred hypotheses are rarely experimentally confirmed.ResultsWe employed cross-kingdom network analyses, applied trait-based functions to the microorganisms, and subsequently experimentally investigated the found putative predator–prey interactions to evaluate whether, and to what extent, correlations indicate actual predator–prey relationships. For this, we investigated algae and their protistan predators in biocrusts of three distinct polar regions, i.e., Svalbard, the Antarctic Peninsula, and Continental Antarctica. Network analyses using FlashWeave indicated that 89, 138, and 51 correlations occurred between predatory protists and algae, respectively. However, trait assignment revealed that only 4.7–9.3% of said correlations link predators to actually suitable prey. We further confirmed these results with HMSC modeling, which resulted in similar numbers of 7.5% and 4.8% linking predators to suitable prey for full co-occurrence and abundance models, respectively. The combination of network analyses and trait assignment increased confidence in the prediction of predator–prey interactions, as we show that 82% of all experimentally investigated correlations could be verified. Furthermore, we found that more vicious predators, i.e., predators with the highest growth rate in co-culture with their prey, exhibit higher stress and betweenness centrality — giving rise to the future possibility of determining important predators from their network statistics.ConclusionsOur results support the idea of using network analyses for inferring predator–prey interactions, but at the same time call for cautionary consideration of the results, by combining them with trait-based approaches to increase confidence in the prediction of biological interactions.FNXjBTWygxbKv-5R-GHg3pVideo

Gender dynamics and academic rank in emergency medicine collaboration networks: A social network and gender propensity analysis

Background: Atrial fibrillation (AF) is affected by both environmental and genetic factors. Previous genetic association studies, especially genome-wide association studies, revealed a large group of AF-associated genes. However, little is known about the functions and interactions of these genes. Moreover, established genetic variants of AF contribute modestly to AF variance, implying that numerous additional AF-associated genetic variations need to be identified. Hence, a systematic network and pathway analysis is needed. Methods: We retrieved all AF-associated genes from genetic association studies in various databases and performed integrative analyses including pathway enrichment analysis, pathway crosstalk analysis, network analysis, and microarray meta-analysis. Results: We collected 254 AF-associated genes from genetic association studies in various databases. Pathway enrichment analysis revealed the top biological pathways that were enriched in the AF-associated genes related to cardiac electromechanical activity. Pathway crosstalk analysis showed that numerous neuro-endocrine-immune pathways connected AF with various diseases including cancers, inflammatory diseases, and cardiovascular diseases. Furthermore, an AF-specific subnetwork was constructed with the prize-collecting Steiner forest algorithm based on the AF-associated genes, and 24 novel genes that were potentially associated with AF were inferred by the subnetwork. In the microarray meta-analysis, six of the 24 novel genes (APLP1, CREB1, CREBBP, PRMT1, IRAK1, and PLXND1) were expressed differentially in patients with AF and sinus rhythm. Conclusions: AF is not only an isolated disease with abnormal electrophysiological activity but might also share a common genetic basis and biological process with tumors and inflammatory diseases as well as cardiovascular diseases. Moreover, the six novel genes inferred from network analysis might help detect the missing AF risk loci.

ObjectivesSocial network analysis focuses on the relationships between people and structures that form through their interactions. Research in the field has shown that people can be influenced by their social...

ObjectivesSocial network analysis focuses on the relationships between people and structures that form through their interactions. Research in the field has shown that people can be influenced by their social...

The effects of data quality on the analysis of corporate board interlock networks

In this paper, we present the first end-to-end fairness analysis of a network of fair servers. We argue that it is difficult to extend existing single-node fairness analysis to an end-to-end analysis of a network where each node may employ a different fair scheduling algorithm. We then present a two-step approach for end-to-end fairness analysis of heterogeneous networks. First, we define a class of scheduling algorithms, referred to as the fair throughput (FT) class, and prove that most known fair scheduling algorithms belong to this class. Second, we develop an analysis methodology for deriving the end-to-end fairness bounds for a network of FT servers. Our analysis is general and can be applied to heterogeneous networks where different nodes employ different scheduling algorithms from the FT class.

The existing work on dependability modelling and analysis of networks have main focuses on the, structural properties. However, the communication networks also have dynamic characteristics and behavioral properties, such as changes of topology, routes, and traffic loads, which should necessarily be reflected in the modelling. We regard the dependability modelling and analysis of IP networks with an intra-domain routing and traffic handling. This yields to an increased complexity in the modelling and analysis, due to the increase of the state space. Several techniques have been proposed to deal with the growth of the state space. To an analyst, an interesting point is, whether he/she can make a trade-off to the factors under consideration, i.e. the model representativeness vs. modelling complexity, and computation efforts vs. result accuracy. To meet these requirements, we propose a modelling approach where failures and repairs of network components as well as routing and traffic handling are described by a set of stochastic activity networks (SAN). The SANs are designed to restrict the generation of the state space to the most probable states, which enables an analysis without creation of an excessively large state space and achieving a sufficient accuracy of the result. A case study based on the Norwegian university IP backbone network demonstrates the applicability of this approach.

Background: The details of molecular mechanisms underlying the differentiation of Mesenchymal Stem Cells (MSCs) into specific lineages are not well understood.Objectives: We aimed to construct the interactome network and topology analysis of bone marrow mesenchymal stem cell of CAGE data. Applying the enrichment results,we wanted to introduce the common genes and hub-microRNA and hub-genes of these giant network.Materials and Methods: In this study, we constructed gene regulatory networks for each non-mesenchymal cell lineage according to their gene expression profiles obtained from FANTOM5 database.The putative interactions of TF-gene and protein-protein were determined using TRED, STRING, HPRD and GeneMANIA servers.In parallel, a regulatory network including corresponding miRNAs and total differentially expressed genes (DEGs) was constructed for each cell lineage. Results: The results indicated that analysis of networks’ topology can significantly distinguish the hub regulatory genes and miRNAs involved in the differentiation of MSCs.The functional annotation of identified hub genes and miRNAs revealed that several signal transduction pathways i.e. AKT, WNT and TGFβ andcell proliferation related pathways play a pivotal role in the regulation of MSCs differentiation. We also classified cell lineages into two groups based on their predicted miRNA profiles. Conclusions: In conclusion, we found a number of hub genes and miRNAs which seem to have key regulatory functions during differentiation of MSCs.Our results also introduce a number of new regulatory genes and miRNAs which can be considered as the new candidates for genetic manipulation of MSCs in vitro.

This chapter describes basic principles for modeling genetic regulatory networks, using three different classes of formalisms: discrete, hybrid, and continuous differential systems. A short review of the mathematical tools for each formalism is presented. Based on several simple examples, which are worked out in detail, this chapter illustrates the study and analysis of the networks’ dynamics, their temporal evolution and asymptotic behaviors.

In order to eliminate hidden problems and prevent failures in power communication network in advance, a reliability analysis and risk warning strategy of power communication network based on SG-EA architecture is proposed, which includes the processes of establishing a common data model for resources, establishing protection relationship model, and risk warning of power communication network. A hierarchical quantitative standard algorithm of communication network risk warning indicators is proposed to clearly and quantitatively classify the levels of communication network risk warning. The indicator warning and indicator-trend warning fusion algorithm is designed to realize the comprehensive analysis of power communication network, so as to obtain the risk warning results of graded disposition. This strategy can use the performance collection and analysis of network and equipment to control the trend of resource changes, so as to arrange proactive and targeted risk pre-control or maintenance work before the occurrence of failure.