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network construction

Jeong-Hyeon Shin, Yu Hyun Um, Chang Uk Lee, Hyun Kook Lim, Joon-Kyung Seong
BACKGROUND: Coordinated and pattern-wise changes in large scale gray matter structural networks reflect neural circuitry dysfunction in late life depression (LLD), which in turn is associated with emotional dysregulation and cognitive impairments. However, due to methodological limitations, there have been few attempts made to identify individual-level structural network properties or sub-networks that are involved in important brain functions in LLD. METHODS: In this study, we sought to construct individual-level gray matter structural networks using average cortical thicknesses of several brain areas to investigate the characteristics of the gray matter structural networks in normal controls and LLD patients...
January 5, 2018: Journal of Affective Disorders
Mingzhe Sun, Yumeng Li, Tianxin Wang, Yanwei Sun, Xiyuan Xu, Zesheng Zhang
The water-soluble polysaccharides extracted from endosperm of Gleditsia japonica var. delavayi seeds (EGSP) were identified as galactomannan having the M/G ratio of 2.54-2.66 and a weight average molecular weight (Mw) of 1913 kDa. The molecular structure of EGSP was determined by periodate oxidation, Smith degradation, methylation, FTIR and NMR spectroscopy. The main chain is composed of β-1,4-d-mannopyranose and the branches composed of single α-1-d-galactopyranose. We had also established a model to speculate the fine structure of galactomannan molecules and given preliminary results...
March 15, 2018: Carbohydrate Polymers
Jimin Yu, Chenchen Yang, Xiaoming Tang, Ping Wang
This paper investigates the H∞ control problems for uncertain linear system over networks with random communication data dropout and actuator saturation. The random data dropout process is modeled by a Bernoulli distributed white sequence with a known conditional probability distribution and the actuator saturation is confined in a convex hull by introducing a group of auxiliary matrices. By constructing a quadratic Lyapunov function, effective conditions for the state feedback-based H∞ controller and the observer-based H∞ controller are proposed in the form of non-convex matrix inequalities to take the random data dropout and actuator saturation into consideration simultaneously, and the problem of non-convex feasibility is solved by applying cone complementarity linearization (CCL) procedure...
January 15, 2018: ISA Transactions
Seung Seog Han, Gyeong Hun Park, Woohyung Lim, Myoung Shin Kim, Jung Im Na, Ilwoo Park, Sung Eun Chang
Although there have been reports of the successful diagnosis of skin disorders using deep learning, unrealistically large clinical image datasets are required for artificial intelligence (AI) training. We created datasets of standardized nail images using a region-based convolutional neural network (R-CNN) trained to distinguish the nail from the background. We used R-CNN to generate training datasets of 49,567 images, which we then used to fine-tune the ResNet-152 and VGG-19 models. The validation datasets comprised 100 and 194 images from Inje University (B1 and B2 datasets, respectively), 125 images from Hallym University (C dataset), and 939 images from Seoul National University (D dataset)...
2018: PloS One
Min Chen, Jiayan Wang, Yingjun Luo, Kailing Huang, Xiaoshun Shi, Yanhui Liu, Jin Li, Zhengfei Lai, Shuya Xue, Haimei Gao, Allen Chen, Dunjin Chen
BACKGROUND: Long non-coding RNAs (lncRNAs) have previously been emerged as key players in a series of biological processes. Dysregulation of lncRNA is correlated to human diseases including neurological disorders. Here, we developed a multi-step bioinformatics analysis to study the functions of a particular Down syndrome-associated gene DSCR9 including the lncRNAs. The method is named correlation-interaction-network (COIN), based on which a pipeline is implemented. Co-expression gene network analysis and biological network analysis results are presented...
January 19, 2018: Human Genomics
Matteo Figliuzzi, Pierre Barrat-Charlaix, Martin Weigt
Global coevolutionary models of homologous protein families, as constructed by direct coupling analysis (DCA), have recently gained popularity in particular due to their capacity to accurately predict residueresidue contacts from sequence information alone, and thereby to facilitate tertiary and quaternary protein structure prediction. More recently, they have also been used to predict fitness effects of aminoacid substitutions in proteins, and to predict evolutionary conserved protein-protein interactions...
January 17, 2018: Molecular Biology and Evolution
Mohsen Sadatsafavi, Hui Xie, Mahyar Etminan, Kate Johnson, J Mark FitzGerald
BACKGROUND: There is minimal evidence on the extent to which the occurrence of a severe acute exacerbation of COPD that results in hospitalization affects the subsequent disease course. Previous studies on this topic did not generate causally-interpretable estimates. Our aim was to use corrected methodology to update previously reported estimates of the associations between previous and future exacerbations in these patients. METHODS: Using administrative health data in British Columbia, Canada (1997-2012), we constructed a cohort of patients with at least one severe exacerbation, defined as an episode of inpatient care with the main diagnosis of COPD based on international classification of diseases (ICD) codes...
2018: PloS One
Minjia Lu, Xingyu Xu, Baohang Xi, Qi Dai, Chenli Li, Li Su, Xiaonan Zhou, Min Tang, Yuhua Yao, Jialiang Yang
RNAs may act as competing endogenous RNAs (ceRNAs), a critical mechanism in determining gene expression regulations in many cancers. However, the roles of ceRNAs in thyroid carcinoma remains elusive. In this study, we have developed a novel pipeline called Molecular Network-based Identification of ceRNA (MNIceRNA) to identify ceRNAs in thyroid carcinoma. MNIceRNA first constructs micro RNA (miRNA)-messenger RNA (mRNA)long non-coding RNA (lncRNA) networks from miRcode database and weighted correlation network analysis (WGCNA), based on which to identify key drivers of differentially expressed RNAs between normal and tumor samples...
January 19, 2018: Genes
Grzegorz Psuj
Nowadays, there is a strong demand for inspection systems integrating both high sensitivity under various testing conditions and advanced processing allowing automatic identification of the examined object state and detection of threats. This paper presents the possibility of utilization of a magnetic multi-sensor matrix transducer for characterization of defected areas in steel elements and a deep learning based algorithm for integration of data and final identification of the object state. The transducer allows sensing of a magnetic vector in a single location in different directions...
January 19, 2018: Sensors
Fu-Zhen Zhou, Li Yan, Shou-Wei Yin, Chuan-He Tang, Xiao-Quan Yang
This work attempted to engineer emulsions' interface using special affinity between proline-rich gliadin and proanthocyanidins (PA), to develop surfactant-free antioxidant Pickering emulsions with digestive-resistant properties. This binding interaction between gliadin and PA benefited the interfacial adsorption of the particles to corn oil droplets. Pickering droplets as building units assembled into interconnected three-dimensional network structure, giving the emulsions viscoelasticity and ultra-stability...
January 19, 2018: Journal of Agricultural and Food Chemistry
Jordan Prox, Tory Smith, Chad Holl, Nick Chehade, Liang Guo
Novel in vitro platforms are currently revolutionizing the study and reconstruction of cellular circuitry to bypass the pertaining obstacles of data retrieval in vivo. While earlier approaches have provided great insights into culturing circuits in planar dissociated cell culture systems, the lack of full control over network activity and formation limits our understanding of their functionality. Thus, integrating various controllable parameters are required in creating a suitable microenvironment including cell patterning, highly-specified electrical and chemical stimuli, and rational circuit formation via logic functions...
January 19, 2018: Journal of Neural Engineering
Sa-Yoon Park, Ji-Hun Park, Hyo-Su Kim, Choong-Yeol Lee, Hae-Jeung Lee, Ki Sung Kang, Chang-Eop Kim
Panax ginseng has been used since ancient times based on the traditional Asian medicine theory and clinical experiences, and currently, is one of the most popular herbs in the world. To date, most of the studies concerning P. ginseng have focused on specific mechanisms of action of individual constituents. However, in spite of many studies on the molecular mechanisms of P. ginseng, it still remains unclear how multiple active ingredients of P. ginseng interact with multiple targets simultaneously, giving the multidimensional effects on various conditions and diseases...
January 2018: Journal of Ginseng Research
M Kähne, I M Sokolov, S Rüdiger
We develop a statistical framework for studying recurrent networks with broad distributions of the number of synaptic links per neuron. We treat each group of neurons with equal input degree as one population and derive a system of equations determining the population-averaged firing rates. The derivation rests on an assumption of a large number of neurons and, additionally, an assumption of a large number of synapses per neuron. For the case of binary neurons, analytical solutions can be constructed, which correspond to steps in the activity versus degree space...
November 2017: Physical Review. E
Zhao Yang, Juan I Perotti, Claudio J Tessone
Hierarchical organization is an important, prevalent characteristic of complex systems; to understand their organization, the study of the underlying (generally complex) networks that describe the interactions between their constituents plays a central role. Numerous previous works have shown that many real-world networks in social, biologic, and technical systems present hierarchical organization, often in the form of a hierarchy of community structures. Many artificial benchmark graphs have been proposed to test different community detection methods, but no benchmark has been developed to thoroughly test the detection of hierarchical community structures...
November 2017: Physical Review. E
Marc Wiedermann, Jonathan F Donges, Jürgen Kurths, Reik V Donner
Complex networks are usually characterized in terms of their topological, spatial, or information-theoretic properties and combinations of the associated metrics are used to discriminate networks into different classes or categories. However, even with the present variety of characteristics at hand it still remains a subject of current research to appropriately quantify a network's complexity and correspondingly discriminate between different types of complex networks, like infrastructure or social networks, on such a basis...
October 2017: Physical Review. E
Alexander Haluszczynski, Ingo Laut, Heike Modest, Christoph Räth
Pearson correlation and mutual information-based complex networks of the day-to-day returns of U.S. S&P500 stocks between 1985 and 2015 have been constructed to investigate the mutual dependencies of the stocks and their nature. We show that both networks detect qualitative differences especially during (recent) turbulent market periods, thus indicating strongly fluctuating interconnections between the stocks of different companies in changing economic environments. A measure for the strength of nonlinear dependencies is derived using surrogate data and leads to interesting observations during periods of financial market crises...
December 2017: Physical Review. E
S S Melnik, O V Usatenko
The main goal of this paper is to develop an estimate for the conditional probability function of random stationary ergodic symbolic sequences with elements belonging to a finite alphabet. We elaborate on a decomposition procedure for the conditional probability function of sequences considered to be high-order Markov chains. We represent the conditional probability function as the sum of multilinear memory function monomials of different orders (from zero up to the chain order). This allows us to introduce a family of Markov chain models and to construct artificial sequences via a method of successive iterations, taking into account at each step increasingly high correlations among random elements...
July 2017: Physical Review. E
Arianna Bottinelli, Rémi Louf, Marco Gherardi
The costs associated to the length of links impose unavoidable constraints to the growth of natural and artificial transport networks. When future network developments cannot be predicted, the costs of building and maintaining connections cannot be minimized simultaneously, requiring competing optimization mechanisms. Here, we study a one-parameter nonequilibrium model driven by an optimization functional, defined as the convex combination of building cost and maintenance cost. By varying the coefficient of the combination, the model interpolates between global and local length minimization, i...
September 2017: Physical Review. E
Jean-Gabriel Young, Giovanni Petri, Francesco Vaccarino, Alice Patania
Simplicial complexes are now a popular alternative to networks when it comes to describing the structure of complex systems, primarily because they encode multinode interactions explicitly. With this new description comes the need for principled null models that allow for easy comparison with empirical data. We propose a natural candidate, the simplicial configuration model. The core of our contribution is an efficient and uniform Markov chain Monte Carlo sampler for this model. We demonstrate its usefulness in a short case study by investigating the topology of three real systems and their randomized counterparts (using their Betti numbers)...
September 2017: Physical Review. E
Mikhail Tikhonov
Ecosystems are commonly conceptualized as networks of interacting species. However, partitioning natural diversity of organisms into discrete units is notoriously problematic and mounting experimental evidence raises the intriguing question whether this perspective is appropriate for the microbial world. Here an alternative formalism is proposed that does not require postulating the existence of species as fundamental ecological variables and provides a naturally hierarchical description of community dynamics...
September 2017: Physical Review. E
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