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network topology

Gerson Rothschild, Uttiya Basu
Intergenic and intragenic enhancers found inside topologically associated regulatory domains (TADs) express noncoding RNAs, known as enhancer RNAs (eRNAs). Recent studies have indicated these eRNAs play a role in gene regulatory networks by controlling promoter and enhancer interactions and topology of higher-order chromatin structure. Misregulation of enhancer and promoter associated noncoding RNAs (ncRNAs) could stabilize deleterious secondary DNA structures, noncoding RNA associated DNA/RNA hybrid formation, and promote collisions of transcription complexes with replisomes...
January 10, 2017: Trends in Genetics: TIG
Hao Xiao, Tianyang Sun, Bo Meng, Lihong Cheng
The rise of global value chains (GVCs) characterized by the so-called "outsourcing", "fragmentation production", and "trade in tasks" has been considered one of the most important phenomena for the 21st century trade. GVCs also can play a decisive role in trade policy making. However, due to the increasing complexity and sophistication of international production networks, especially in the equipment manufacturing industry, conventional trade statistics and the corresponding trade indicators may give us a distorted picture of trade...
2017: PloS One
Jack McKay Fletcher, Thomas Wennekers
It is clear that the topological structure of a neural network somehow determines the activity of the neurons within it. In the present work, we ask to what extent it is possible to examine the structural features of a network and learn something about its activity? Specifically, we consider how the centrality (the importance of a node in a network) of a neuron correlates with its firing rate. To investigate, we apply an array of centrality measures, including In-Degree, Closeness, Betweenness, Eigenvector, Katz, PageRank, Hyperlink-Induced Topic Search (HITS) and NeuronRank to Leaky-Integrate and Fire neural networks with different connectivity schemes...
November 16, 2016: International Journal of Neural Systems
Laurie M Baker, Sarah Cooley, Ryan P Cabeen, David H Laidlaw, John A Joska, Jacqueline Hoare, Dan J Stein, Jodi Heaps-Woodruff, Lauren E Salminen, Robert H Paul
Infection with human immunodeficiency virus (HIV) is associated with neuroimaging alterations. However, little is known about the topological organization of whole-brain networks and the corresponding association with cognition. As such, we examined structural whole-brain white matter connectivity patterns and cognitive performance in 29 HIV+ young adults (mean age = 25.9) with limited or no HIV treatment history. HIV+ participants and demographically similar HIV- controls (n = 16) residing in South Africa underwent magnetic resonance imaging (MRI) and neuropsychological testing...
January 11, 2017: Brain Connectivity
Fabrizio De Vico Fallani, Vito Latora, Mario Chavez
In many biological systems, the network of interactions between the elements can only be inferred from experimental measurements. In neuroscience, non-invasive imaging tools are extensively used to derive either structural or functional brain networks in-vivo. As a result of the inference process, we obtain a matrix of values corresponding to a fully connected and weighted network. To turn this into a useful sparse network, thresholding is typically adopted to cancel a percentage of the weakest connections...
January 11, 2017: PLoS Computational Biology
Varsha Embar, Adam Handen, Madhavi K Ganapathiraju
When a set of genes are identified to be related to a disease, say through gene expression analysis, it is common to examine the average distance among their protein products in the human interactome as a measure of biological relatedness of these genes. The reasoning for this is that, genes associated with a disease would tend to be functionally related, and that functionally related genes would be closely connected to each other in the interactome. Typically, average shortest path length (ASPL) of disease genes (although referred to as genes in the context of disease-associations, the interactions are among protein-products of these genes) is compared to ASPL of randomly selected genes or to ASPL in a randomly permuted network...
December 2016: Journal of Bioinformatics and Computational Biology
Deborah A Weighill, Daniel Jacobson
We explore the use of a network meta-modeling approach to compare the effects of similarity metrics used to construct biological networks on the topology of the resulting networks. This work reviews various similarity metrics for the construction of networks and various topology measures for the characterization of resulting network topology, demonstrating the use of these metrics in the construction and comparison of phylogenomic and transcriptomic networks.
January 10, 2017: Advances in Biochemical Engineering/biotechnology
C Simitzi, A Ranella, E Stratakis
: Unlike other tissue types, like epithelial tissue, which consist of cells with a much more homogeneous structure and function, the nervous tissue spans in a complex multilayer environment whose topographical features display a large spectrum of morphologies and size scales. Traditional cell cultures, which are based on two-dimensional cell-adhesive culture dishes or coverslips, are lacking topographical cues and mainly simulate the biochemical microenvironment of the cells. With the emergence of micro- and nano-fabrication techniques new types of cell culture platforms are developed, where the effect of various topographical cues on cellular morphology, proliferation and differentiation, can be studied...
January 6, 2017: Acta Biomaterialia
Jie Gao, Claire Tang, Andrew M Smith, Aline Fiona Miller, Alberto Saiani
Self-assembling peptide based hydrogels have encountered increasing interest in the recent years as scaffolds for 3D cell culture or for controlled drug delivery. One of the main challenges is the fine control of the mechanical properties of these materials. The bulk properties of hydrogel not only depend on the intrinsic properties of the fibres but also on the network topology formed. In this work we show how fibre-fibre interactions can be manipulated by design to control the final hydrogels network topology and therefore control the final properties of the material...
January 9, 2017: Biomacromolecules
David Caballero, Josep Samitier
The interaction of cells with their natural environment influences a large variety of cellular phenomena, including cell adhesion, proliferation, and migration. The complex extracellular matrix network has challenged the attempts to replicate in vitro the heterogeneity of the cell environment and has threatened, in general, the relevance of in vitro studies. In this work, we describe a new and extremely versatile approach to generate native-like extracellular matrices with controlled morphologies for the in vitro study of cellular processes...
January 9, 2017: ACS Applied Materials & Interfaces
Zichuang Yan, Yongjing Liu, Yunzhen Wei, Ning Zhao, Qiang Zhang, Cheng Wu, Zhiqiang Chang, Yan Xu
Copy number alteration (CNA) represents an important class of genetic variations that may contribute to tumorigenesis, tumor growth and metastatic spread. CNA can directly affect the expression of genes within the CNA regions; however, genes within the CNA regions exhibit heterogeneity in gene dosage sensitivity. In this study, a computational framework was built to identify 1170 dosage-sensitive genes (DSGs) and 1215 dosage-resistant genes (DRGs) that were related to ovarian serous cystadenocarcinoma (OV) through the association between CNA and gene expression...
January 9, 2017: Molecular BioSystems
Tiago A Schieber, Laura Carpi, Albert Díaz-Guilera, Panos M Pardalos, Cristina Masoller, Martín G Ravetti
Identifying and quantifying dissimilarities among graphs is a fundamental and challenging problem of practical importance in many fields of science. Current methods of network comparison are limited to extract only partial information or are computationally very demanding. Here we propose an efficient and precise measure for network comparison, which is based on quantifying differences among distance probability distributions extracted from the networks. Extensive experiments on synthetic and real-world networks show that this measure returns non-zero values only when the graphs are non-isomorphic...
January 9, 2017: Nature Communications
Man Xu, Xiangliang Tan, Xinyuan Zhang, Yihao Guo, Yingjie Mei, Qianjin Feng, Yikai Xu, Yanqiu Feng
PURPOSE: Systemic lupus erythematosus (SLE) is a chronic inflammatory female-predominant autoimmune disease that can affect the central nervous system and exhibit neuropsychiatric symptoms. In SLE patients without neuropsychiatric symptoms (non-NPSLE), recent diffusion tensor imaging studies showed white matter abnormalities in their brains. The present study investigated the entire brain white matter structural connectivity in non-NPSLE patients by using probabilistic tractography and connectivity-based analyses...
2017: NeuroImage: Clinical
Santiago Videla, Julio Saez-Rodriguez, Carito Guziolowski, Anne Siegel
: We introduce the caspo toolbox, a python package implementing a workflow for reasoning on logical networks families. Our software allows researchers to (i) LEARN: a family of logical networks derived from a given topology and explaining the experimental response to various perturbations; (ii) CLASSIFY: all logical networks in a given family by their input-output behaviors; (iii) PREDICT: the response of the system to every possible perturbation based on the ensemble of predictions; (iv) DESIGN: new experimental perturbations to discriminate among a family of logical networks; and (v) CONTROL: a family of logical networks by finding all interventions strategies forcing a set of targets into a desired steady state...
January 8, 2017: Bioinformatics
Guanjing Hu, Ran Hovav, Corrinne E Grover, Adi Faigenboim-Doron, Noa Kadmon, Justin T Page, Joshua A Udall, Jonathan F Wendel
The cotton genus (Gossypium) provides a superior system for the study of diversification, genome evolution, polyploidization, and human-mediated selection. To gain insight into phenotypic diversification in cotton seeds, we conducted coexpression network analysis of developing seeds from diploid and allopolyploid cotton species and explored network properties. Key network modules and functional associations were identified related to seed oil content and seed weight. We compared species-specific networks to reveal topological changes, including rewired edges and differentially coexpressed genes, associated with speciation, polyploidy, and cotton domestication...
January 6, 2017: Genome Biology and Evolution
Vijay Badrinarayanan, Alex Kendall, Roberto Cipolla
We present a novel and practical deep fully convolutional neural network architecture for semantic pixel-wise segmentation termed SegNet. This core trainable segmentation engine consists of an encoder network, a corresponding decoder network followed by a pixel-wise classification layer. The architecture of the encoder network is topologically identical to the 13 convolutional layers in the VGG16 network [1]. The role of the decoder network is to map the low resolution encoder feature maps to full input resolution feature maps for pixel-wise classification...
January 2, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
Toshikazu Kawagoe, Keiichi Onoda, Shuhei Yamaguchi
Aging is associated with deterioration in a number of cognitive functions. Previous reports have demonstrated the beneficial effect of physical fitness on cognitive function, especially executive function (EF). The graph theoretical approach models the brain as a complex network represented graphically as nodes and edges. We analyzed several measures of EF, an index of physical fitness, and resting-state functional magnetic resonance imaging data from healthy older volunteers to elucidate the associations among EF, cardiorespiratory fitness, and brain network properties...
January 5, 2017: Scientific Reports
Peter N Taylor, Yujiang Wang, Marcus Kaiser
Previous structural brain connectivity studies have mainly focussed on the macroscopic scale of around 1,000 or fewer brain areas (network nodes). However, it has recently been demonstrated that high resolution structural connectomes of around 50,000 nodes can be generated reproducibly. In this study, we infer high resolution brain connectivity matrices using diffusion imaging data from the Human Connectome Project. With such high resolution we are able to analyse networks within brain areas in a single subject...
January 5, 2017: Scientific Reports
Guohua Yu, Yanqiong Zhang, Weiqiong Ren, Ling Dong, Junfang Li, Ya Geng, Yi Zhang, Defeng Li, Haiyu Xu, Hongjun Yang
For decades in China, the Yin-Huang-Qing-Fei capsule (YHQFC) has been widely used in the treatment of chronic bronchitis, with good curative effects. Owing to the complexity of traditional Chinese herbal formulas, the pharmacological mechanism of YHQFC remains unclear. To address this problem, a network pharmacology-based strategy was proposed in this study. At first, the putative target profile of YHQFC was predicted using MedChem Studio, based on structural and functional similarities of all available YHQFC components to the known drugs obtained from the DrugBank database...
2017: International Journal of Chronic Obstructive Pulmonary Disease
Taylor Bolt, Jason S Nomi, Mikail Rubinov, Lucina Q Uddin
Much of the literature exploring differences between intrinsic and task-evoked brain architectures has examined changes in functional connectivity patterns between specific brain regions. While informative, this approach overlooks important overall functional changes in hub organization and network topology that may provide insights about differences in integration between intrinsic and task-evoked states. Examination of changes in overall network organization, such as a change in the concentration of hub nodes or a quantitative change in network organization, is important for understanding the underlying processes that differ between intrinsic and task-evoked brain architectures...
January 4, 2017: Human Brain Mapping
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