An Improved Capsule Network Based on Newly Reconstructed Network and the Method of Sharing Parameters

2019 ◽  
pp. 116-123
Author(s):  
Chunyan Lu ◽  
Shukai Duan ◽  
Lidan Wang
Keyword(s):  
Reconstructed Network

scholarly journals Reconstruction of Protein-Protein Interaction Network of Insulin Signaling inHomo Sapiens

2010 ◽  
Vol 2010 ◽  
pp. 1-7 ◽  
Author(s):  
Saliha Durmuş Tekir ◽  
Pelin Ümit ◽  
Aysun Eren Toku ◽  
Kutlu Ö. Ülgen
Keyword(s):  
Type 2 Diabetes ◽  
Insulin Signaling ◽  
Homo Sapiens ◽  
Interaction Network ◽  
Protein Protein Interaction ◽  
Signaling Mechanisms ◽  
Reconstructed Network ◽  
Protein Protein Interaction Network

Diabetes is one of the most prevalent diseases in the world. Type 1 diabetes is characterized by the failure of synthesizing and secreting of insulin because of destroyed pancreaticβ-cells. Type 2 diabetes, on the other hand, is described by the decreased synthesis and secretion of insulin because of the defect in pancreaticβ-cells as well as by the failure of responding to insulin because of malfunctioning of insulin signaling. In order to understand the signaling mechanisms of responding to insulin, it is necessary to identify all components in the insulin signaling network. Here, an interaction network consisting of proteins that have statistically high probability of being biologically related to insulin signaling inHomo sapienswas reconstructed by integrating Gene Ontology (GO) annotations and interactome data. Furthermore, within this reconstructed network, interacting proteins which mediate the signal from insulin hormone to glucose transportation were identified using linear paths. The identification of key components functioning in insulin action on glucose metabolism is crucial for the efforts of preventing and treating type 2 diabetes mellitus.

scholarly journals On the influence of spatial sampling on climate networks

2014 ◽  
Vol 21 (3) ◽  
pp. 651-657 ◽  
Author(s):  
N. Molkenthin ◽  
K. Rehfeld ◽  
V. Stolbova ◽  
L. Tupikina ◽  
J. Kurths
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Voronoi Cell ◽  
Spatial Sampling ◽  
Series Data ◽  
Cell Size Distribution ◽  
Reconstructed Network ◽  
Climate Time Series ◽  
The Impact ◽  
Climate Networks

Abstract. Climate networks are constructed from climate time series data using correlation measures. It is widely accepted that the geographical proximity, as well as other geographical features such as ocean and atmospheric currents, have a large impact on the observable time-series similarity. Therefore it is to be expected that the spatial sampling will influence the reconstructed network. Here we investigate this by comparing analytical flow networks, networks generated with the START model and networks from temperature data from the Asian monsoon domain. We evaluate them on a regular grid, a grid with added random jittering and two variations of clustered sampling. We find that the impact of the spatial sampling on most network measures only distorts the plots if the node distribution is significantly inhomogeneous. As a simple diagnostic measure for the detection of inhomogeneous sampling we suggest the Voronoi cell size distribution.

scholarly journals miRNA–mRNA network involved in folliculogenesis interactome: systems biology approach

Reproduction ◽  
2017 ◽  
Vol 154 (1) ◽  
pp. 51-65 ◽  
Author(s):  
Abolfazl Bahrami ◽  
Seyed Reza Miraie-Ashtiani ◽  
Mostafa Sadeghi ◽  
Ali Najafi
Keyword(s):  
Granulosa Cells ◽  
Regulatory Networks ◽  
Ovarian Follicle ◽  
Transcriptome Profiling ◽  
Computational Method ◽  
Bipartite Network ◽  
Data Sets ◽  
Target Mrnas ◽  
Master List ◽  
Reconstructed Network

At later phases of folliculogenesis, the mammalian ovarian follicle contains layers of granulosa cells surrounding an antral cavity. To better understand the molecular basis of follicular growth and granulosa cell maturation, we study transcriptome profiling of granulosa cells from small (<5 mm) and large (>10 mm) bovine follicles using simultaneous method of Affymetrix microarrays (24,128 probe sets) and RNA-Seq data sets. This study proposes a computational method to discover the functional miRNA–mRNA regulatory modules, that is, groups of miRNAs and their target mRNAs that are believed to take part cooperatively in post-transcriptional gene regulation under specific conditions. The reconstructed network was named Integrated miRNA–mRNA Bipartite Network. 277 genes and 6 key modules were disclosed through clustering for mRNA master list. The 66 genes are among the genes that belong to at least two modules. All these genes, being involved in at least one of the phenomena, namely cell survival, proliferation, metastasis and apoptosis, have an overexpression pattern (P < 0.01). For miRNA master list, a total of 172 sequences were differentially expressed (P < 0.01) between dominant (large) and each of subordinate (small) follicles. Within the follicle, these miRNAs were predominantly expressed in mural granulosa cells. Finally, predicted and validated targets of these miRNAs enriched in dominant (large) follicles were identified, which are mapped to signaling pathways involved in follicular cell proliferation, steroidogenesis, PI3K/AKT/mTOR and Ras/Raf/MEK/ERK. The identification of miRNAs and their target mRNAs and the construction of their regulatory networks may give new insights into biological procedures.

Identification of drug efficacy change using reconstructed network altered by SNPs on pathway gene

2018 ◽  
Vol 21 (2) ◽  
pp. 107
Author(s):  
Youngmi Yoon ◽  
Soyoun Hwang ◽  
Sukyung Seo ◽  
Giup Jang ◽  
Taekeon Lee
Keyword(s):  
Drug Efficacy ◽  
Pathway Gene ◽  
Reconstructed Network

Identification of drug efficacy change using reconstructed network altered by SNPs on pathway gene

2018 ◽  
Vol 21 (2) ◽  
pp. 107
Author(s):  
Sukyung Seo ◽  
Taekeon Lee ◽  
Giup Jang ◽  
Soyoun Hwang ◽  
Youngmi Yoon
Keyword(s):  
Drug Efficacy ◽  
Pathway Gene ◽  
Reconstructed Network

scholarly journals Systemic Risk Contagion in Reconstructed Financial Credit Network within Banking and Firm Sectors on DebtRank Based Model

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Yuetang (Peter) Bian ◽  
Yu Wang ◽  
Lu Xu
Keyword(s):  
Systemic Risk ◽  
Computational Simulation ◽  
Balance Sheet ◽  
Nonlinear Behavior ◽  
Influential Factors ◽  
Counterparty Risk ◽  
Negative Effects ◽  
Reconstructed Network ◽  
Negative Effect ◽  
Credit Network

This paper is dedicated to building a multilayer financial network within banking sectors and firm sectors (nonbanking) on the balance sheet of two types of agents and to assessing systemic risk contagion in the reconstructed network. Two propagation channels due to interbank credit and counterparty risk via banks’ loans to firms are comprehensively taken into account in systemic risk contagion assessment, which is based on the DebtRank model by analyzing the relative loss of each bank’s equity and the vulnerability of the network. The computational simulation on how systemic risk contagious process evolves has been conducted, where the possible influential factors of network structure, agent’s initial risk status, external shock ratio, liquidity flow rate, and different layers of the network are considered. The findings show that the reconstructed network is absolutely vulnerable under the assumed market circumstance without any bailouts and the risk contagion process shows nonlinear behavior. Specifically, when the average degree of the network and the external shock ratio increases, the risk contagion speed becomes relatively high and the resulting negative effects on the network are more intense. Besides, risks originating from the failed firms in bank-firm layer should place more negative effect on the financial system than that only happening in interbank market. Different liquidity rates in financial market could lead to obvious discrepancy of the risk contagion speed and the extent of asset loss. Additionally, the two layers of the network have diverse influences on risk contagious process resulting in totally different banks’ status in each layer.

Interactive Wormhole Detection and Evaluation

2007 ◽  
Vol 6 (1) ◽  
pp. 3-17 ◽  
Author(s):  
Weichao Wang ◽  
Aidong Lu
Keyword(s):  
Wireless Networks ◽  
Large Scale ◽  
Network Performance ◽  
Visual Analysis ◽  
Detection Algorithm ◽  
False Alarms ◽  
Detection Accuracy ◽  
User Interactions ◽  
Wormhole Attacks ◽  
Reconstructed Network

Wormhole attacks in wireless networks can severely deteriorate network performance and compromise security through spoiling the routing protocols and weakening the security enhancements. This paper develops an approach, interactive visualization of wormholes (IVoW), to monitor and detect such attacks in large-scale wireless networks in real time. We characterize the topology features of a network under wormhole attacks through the node position changes and visualize the information at dynamically adjusted scales. We integrate an automatic detection algorithm with appropriate user interactions to handle complicated scenarios that include a large number of moving nodes and multiple wormhole attackers. Various visual forms have been adopted to assist in the understanding and analysis of reconstructed network topology and to improve the detection accuracy. Extended simulation has demonstrated that the proposed approach can effectively locate the fake neighbor connections without introducing many false alarms. IVoW does not require the wireless nodes to be equipped with any special hardware, thus avoiding any additional cost. We have performed user studies to evaluate the effectiveness of our approach and demonstrate that visual analysis can be successfully combined with network security mechanisms to greatly improve intrusion detection capabilities.

scholarly journals The First Reconstruction of Intercellular Interaction Network in Mus musculus Immune System

2019 ◽  
Author(s):  
Somayeh Azadian ◽  
Javad Zahiri ◽  
Seyed Shahriar Arab ◽  
Reza Hassan sajedi
Keyword(s):  
Stromal Cells ◽  
Interaction Network ◽  
High Specificity ◽  
Genome Project ◽  
Intercellular Interaction ◽  
Ligand Interaction ◽  
Intercellular Interactions ◽  
Genes Expression ◽  
Ligand Interactions ◽  
Reconstructed Network

AbstractIntercellular interactions play an important role in regulating communications of cells with each other. So far, many studies have been done with both experimental and computational approaches in this field. Therefore, in order to investigate and analyze the intercellular interactions, use of network reconstruction has attracted the attention of many researchers recently. The intercellular interaction network was reconstructed using receptor and ligand interaction dataset and gene expression data of the first phase of the immunological genome project. In the reconstructed network, there are 9271 communications between 162 cells which were created through 460 receptor-ligand interactions. The results indicate that cells of hematopoietic lineages use fewer communication pathways for interacting with each other and the most network communications belong to non-hematopoietic stromal cells and macrophages. The results indicated the importance of the communication of stromal cells with immune cells and also high specificity of genes expression in these cells. The stromal cells have the most autocrine communication, and interactions between the wnt5a with the Ror1/2 and Fzd5a among the stromal lineage cells are abundant.

Chloroplast DNA phylogeography of Cunninghamia konishii (Cupressaceae), an endemic conifer of Taiwan

Genome ◽  
2001 ◽  
Vol 44 (5) ◽  
pp. 797-807 ◽  
Author(s):  
Sheng-You Lu ◽  
Ching-I Peng ◽  
Yu-Ping Cheng ◽  
Kuo-Hsiang Hong ◽  
Tzen-Yuh Chiang
Keyword(s):  
Chloroplast Dna ◽  
Dna Sequences ◽  
Mainland China ◽  
Migration Routes ◽  
Phylogeographic Pattern ◽  
Long Distance ◽  
Organelle Dna ◽  
Reconstructed Network ◽  
Minimum Spanning Network ◽  
Pool Model

In this study, we investigated the genetic structure and phylogeographic pattern of the genus Cunninghamia, a member of the Cupressaceae restricted to mainland China and Taiwan, based on sequences of the trnD–trnT noncoding spacer of the chloroplast DNA. Maternal inheritance of chloroplasts was determined experimentally. No paternal leakage was detected. Both parsimony and neighbor-joining analyses revealed the polyphyly of Cunninghamia konishii, populations of which were nested in clades of C. lanceolata from mainland China. The nucleotide diversity of chloroplast DNA sequences within C. konishii (0.0118) was higher than that between species (0.0104), which agrees with a previous allozyme investigation. Based on mutational differences between sequences, a minimum spanning network consisting of five clades was constructed. Significant genetic differentiation (ΦST = 0.130, P < 0.001) was detected between the clades based on AMOVA analyses. We infer several possible refugia in the Yunnan, Zhejiang, and Guangdong provinces of south China, all located in the minimum network as interior nodes. We also infer possible migration routes of Cunninghamia populations. The phylogeographic pattern shown in the reconstructed network suggests that the present-day Cunninghamia populations in Taiwan were derived from six different sources in continental Asia via long-distance seed dispersal. A migrant-pool model explains the heterogeneous composition of the organelle DNA in Taiwan's populations and the low differentiation between populations of Taiwan and China (ΦCT = 0.012, P = 0.454). In contrast with the genetic heterogeneity within geographic populations, many local populations have attained coalescence at the trnD–trnT alleles, which has led to significant differentiation at the population level.Key words: AMOVA, coalescence, cpDNA, Cunninghamia konishii, Cunninghamia lanceolata, minimum spanning network, phylogeography.

scholarly journals Gut content metabarcoding reveals potential importance of fisheries discards consumption in marine fauna

2021 ◽  
Author(s):  
Benjamin Lejeune ◽  
Maud Aline Mouchet ◽  
Sonia Mehault ◽  
Dorothée Kopp
Keyword(s):  
Ecosystem Approach ◽  
Gut Contents ◽  
The European Union ◽  
Fish Prey ◽  
Marine Fauna ◽  
Marine Food Webs ◽  
Dna Metabarcoding ◽  
Fisheries Policy ◽  
Reconstructed Network ◽  
Marine Food

Fisheries discards have become a source of concern for the perennation of marine resources. To reduce discards, the European Union adopted a Landing Obligation under the reform of its Common Fisheries Policy. However, food web consequences of reducing discards remain uncertain since their degree and pathway of reintegration are understudied. We used multi-marker DNA metabarcoding of gut contents and an ecological network approach to quantify marine fauna reliance on discarded fish and functional importance of discard consumers in coastal fishing grounds. We show that potential discard consumption is widespread across fish and invertebrates, but particularly important for decapods which were also pinpointed as functionally important. Potential discard consumption may represent up to 66% of all interactions involving fish prey in the reconstructed network. We highlight that discard reliance may be more important than previously assessed in some fishing areas and support functionally important taxa. While reducing discarding remains a conservation priority, it is crucial to understand discards reintegration in marine food webs to anticipate changes in the context of an ecosystem approach to fisheries management.

Sign in / Sign up

Export Citation Format

Share Document