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Network-based inference

Saeed Reza Kheradpisheh, Mohammad Ganjtabesh, Simon J Thorpe, Timothée Masquelier
Previous studies have shown that spike-timing-dependent plasticity (STDP) can be used in spiking neural networks (SNN) to extract visual features of low or intermediate complexity in an unsupervised manner. These studies, however, used relatively shallow architectures, and only one layer was trainable. Another line of research has demonstrated - using rate-based neural networks trained with back-propagation - that having many layers increases the recognition robustness, an approach known as deep learning. We thus designed a deep SNN, comprising several convolutional (trainable with STDP) and pooling layers...
December 23, 2017: Neural Networks: the Official Journal of the International Neural Network Society
Heeju Noh, Jason E Shoemaker, Rudiyanto Gunawan
Genome-wide transcriptional profiling provides a global view of cellular state and how this state changes under different treatments (e.g. drugs) or conditions (e.g. healthy and diseased). Here, we present ProTINA (Protein Target Inference by Network Analysis), a network perturbation analysis method for inferring protein targets of compounds from gene transcriptional profiles. ProTINA uses a dynamic model of the cell-type specific protein-gene transcriptional regulation to infer network perturbations from steady state and time-series differential gene expression profiles...
January 9, 2018: Nucleic Acids Research
Zhiwei Ji, Bing Wang, Ke Yan, Ligang Dong, Guanmin Meng, Lei Shi
BACKGROUND: In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc...
December 21, 2017: BMC Systems Biology
Pedro Urbano Alves, Raquel Vinhas, Alexandra R Fernandes, Semra Zuhal Birol, Levent Trabzon, Iwona Bernacka-Wojcik, Rui Igreja, Paulo Lopes, Pedro Viana Baptista, Hugo Águas, Elvira Fortunato, Rodrigo Martins
Many diseases have their treatment options narrowed and end up being fatal if detected during later stages. As a consequence, point-of-care devices have an increasing importance for routine screening applications in the health sector due to their portability, fast analyses and decreased cost. For that purpose, a multifunctional chip was developed and tested using gold nanoprobes to perform RNA optical detection inside a microfluidic chip without the need of molecular amplification steps. As a proof-of-concept, this device was used for the rapid detection of chronic myeloid leukemia, a hemato-oncological disease that would benefit from early stage diagnostics and screening tests...
January 10, 2018: Scientific Reports
Vahideh Rafiei, Ziaeddin Banihashemi, Laura S Bautista-Jalon, María Del Mar Jiménez-Gasco, Gillian Turgeon, Michael G Milgroom
Verticillium dahliae is a plant pathogenic fungus that reproduces asexually and its population structure is highly clonal. In the present study, 78 V. dahliae isolates from Iran were genotyped for mating type, SNPs and microsatellites to assign them to clonal lineages and to determine population genetic structure in Iran. The mating type of all isolates was MAT1-2. Based on neighbor-joining analysis and minimum spanning networks constructed from SNPs and microsatellite genotypes, all but four isolates were assigned to lineage 2B824; four isolates were assigned to lineage 4B...
January 10, 2018: Phytopathology
Miao Hu, Catherine E Graves, Can Li, Yunning Li, Ning Ge, Eric Montgomery, Noraica Davila, Hao Jiang, R Stanley Williams, J Joshua Yang, Qiangfei Xia, John Paul Strachan
Using memristor crossbar arrays to accelerate computations is a promising approach to efficiently implement algorithms in deep neural networks. Early demonstrations, however, are limited to simulations or small-scale problems primarily due to materials and device challenges that limit the size of the memristor crossbar arrays that can be reliably programmed to stable and analog values, which is the focus of the current work. High-precision analog tuning and control of memristor cells across a 128 × 64 array is demonstrated, and the resulting vector matrix multiplication (VMM) computing precision is evaluated...
January 10, 2018: Advanced Materials
Pieter Albers, Bram Weytjens, René De Mot, Kathleen Marchal, Dirk Springael
The proteobacteria Variovorax sp. WDL1, Comamonas testosteroni WDL7, and Hyphomicrobium sulfonivorans WDL6 compose a triple-species consortium that synergistically degrades and grows on the phenylurea herbicide linuron. To acquire a better insight into the interactions between the consortium members and the underlying molecular mechanisms, we compared the transcriptomes of the key biodegrading strains WDL7 and WDL1 grown as biofilms in either isolation or consortium conditions by differential RNAseq analysis...
January 3, 2018: MicrobiologyOpen
Pavel Skums, Alex Zelikovsky, Rahul Singh, Walker Gussler, Zoya Dimitrova, Sergey Knyazev, Igor Mandric, Sumathi Ramachandran, David Campo, Deeptanshu Jha, Leonid Bunimovich, Elizabeth Costenbader, Connie Sexton, Siobhan O'Connor, Guo-Liang Xia, Yury Khudyakov
Motivation: Genomic analysis has become one of the major tools for disease outbreak investigations. However, existing computational frameworks for inference of transmission history from viral genomic data often do not consider intra-host diversity of pathogens and heavily rely on additional epidemiological data, such as sampling times and exposure intervals. This impedes genomic analysis of outbreaks of highly mutable viruses associated with chronic infections, such as human immunodeficiency virus and hepatitis C virus, whose transmissions are often carried out through minor intra-host variants, while the additional epidemiological information often is either unavailable or has a limited use...
January 1, 2018: Bioinformatics
Dan Li, William Yang, Jialing Zhang, Jack Y Yang, Renchu Guan, Mary Qu Yang
Lung cancer is the second most commonly diagnosed carcinoma and is the leading cause of cancer death. Although significant progress has been made towards its understanding and treatment, unraveling the complexities of lung cancer is still hampered by a lack of comprehensive knowledge on the mechanisms underlying the disease. High-throughput and multidimensional genomic data have shed new light on cancer biology. In this study, we developed a network-based approach integrating somatic mutations, the transcriptome, DNA methylation, and protein-DNA interactions to reveal the key regulators in lung adenocarcinoma (LUAD)...
January 5, 2018: Genes
Hamid Beiki, Abbas Pakdel, Ardeshir Nejati Javaremi, Ali Masoudi-Nejad, James M Reecy
BACKGROUND: Weighted Gene Co-expression Network analysis, a powerful technique used to extract co-expressed gene pattern from mRNA expression data, was constructed to infer common immune strategies used by cattle in response to five different bacterial species (Escherichia coli, Mycobacterium avium, Mycobacterium bovis, Salmonella and Staphylococcus aureus) and a protozoa (Trypanosoma Congolense) using 604 publicly available gene expression microarrays from 12 cattle infection experiments...
January 5, 2018: BMC Immunology
Zhen Tian, Maozu Guo, Chunyu Wang, LinLin Xing, Lei Wang, Yin Zhang
BACKGROUND: Discovering novel genes that are involved human diseases is a challenging task in biomedical research. In recent years, several computational approaches have been proposed to prioritize candidate disease genes. Most of these methods are mainly based on protein-protein interaction (PPI) networks. However, since these PPI networks contain false positives and only cover less half of known human genes, their reliability and coverage are very low. Therefore, it is highly necessary to fuse multiple genomic data to construct a credible gene similarity network and then infer disease genes on the whole genomic scale...
September 20, 2017: Journal of Biomedical Semantics
Christoph Schmidt, Diana Piper, Britta Pester, Andreas Mierau, Herbert Witte
Identification of module structure in brain functional networks is a promising way to obtain novel insights into neural information processing, as modules correspond to delineated brain regions in which interactions are strongly increased. Tracking of network modules in time-varying brain functional networks is not yet commonly considered in neuroscience despite its potential for gaining an understanding of the time evolution of functional interaction patterns and associated changing degrees of functional segregation and integration...
October 20, 2017: International Journal of Neural Systems
Alfonso Castro, Andrés A Sedano, Fco Javier García, Eduardo Villoslada, Víctor A Villagrá
Nowadays, the complexity of global video products has substantially increased. They are composed of several associated services whose functionalities need to adapt across heterogeneous networks with different technologies and administrative domains. Each of these domains has different operational procedures; therefore, the comprehensive management of multi-domain services presents serious challenges. This paper discusses an approach to service management linking fault diagnosis system and Business Processes for Telefónica's global video service...
December 28, 2017: Sensors
Christine Johnston, Amalia Magaret, Pavitra Roychoudhury, Alexander L Greninger, Daniel Reeves, Joshua Schiffer, Keith R Jerome, Cassandra Sather, Kurt Diem, Jairam R Lingappa, Connie Celum, David M Koelle, Anna Wald
BACKGROUND: Quantitative estimation of the extent to which the immune system's protective effect against one herpes simplex virus type 2 (HSV-2) infection protects against infection with additional HSV-2 strains is important for understanding the potential for HSV-2 vaccine development. Using viral genotyping, we estimated the prevalence of HSV-2 dual-strain infection and identified risk factors. METHODS AND FINDINGS: People with and without HIV infection participating in HSV-2 natural history studies (University of Washington Virology Research Clinic) and HIV prevention trials (HIV Prevention Trials Network 039 and Partners in Prevention HSV/HIV Transmission Study) in the US, Africa, and Peru with 2 genital specimens each containing ≥105 copies herpes simplex virus DNA/ml collected a median of 5 months apart (IQR: 2-11 months) were included...
December 2017: PLoS Medicine
Alyssa Imbert, Armand Valsesia, Caroline Le Gall, Claudia Armenise, Gregory Lefebvre, Pierre-Antoine Gourraud, Nathalie Viguerie, Nathalie Villa-Vialaneix
Motivation: Network inference provides a global view of the relations existing between gene expression in a given transcriptomic experiment (often only for a restricted list of chosen genes). However, it is still a challenging problem: even if the cost of sequencing techniques has decreased over the last years, the number of samples in a given experiment is still (very) small compared to the number of genes. Results: We propose a method to increase the reliability of the inference when RNA-seq expression data have been measured together with an auxiliary dataset that can provide external information on gene expression similarity between samples...
December 21, 2017: Bioinformatics
Yu Zhao, Shu Zhang, Hanbo Chen, Wei Zhang, Lv Jinglei, Xi Jiang, Dinggang Shen, Tianming Liu
Accurate registration plays a critical role in group-wise functional Magnetic Resonance Imaging (fMRI) image analysis, as spatial correspondence among different brain images is a prerequisite for inferring meaningful patterns. However, the problem is challenging and remains open, and more effort should be made to advance the state-of-the-art image registration methods for fMRI images. Inspired by the observation that common functional networks can be reconstructed from fMRI image across individuals, we propose a novel computational framework for simultaneous groupwise fMRI image registration by utilizing those common functional networks as references for spatial alignments...
April 2017: Proceedings of the IEEE International Symposium on Biomedical Imaging: from Nano to Macro
Yang Liu, Perry Palmedo, Qing Ye, Bonnie Berger, Jian Peng
While genes are defined by sequence, in biological systems a protein's function is largely determined by its three-dimensional structure. Evolutionary information embedded within multiple sequence alignments provides a rich source of data for inferring structural constraints on macromolecules. Still, many proteins of interest lack sufficient numbers of related sequences, leading to noisy, error-prone residue-residue contact predictions. Here we introduce DeepContact, a convolutional neural network (CNN)-based approach that discovers co-evolutionary motifs and leverages these patterns to enable accurate inference of contact probabilities, particularly when few related sequences are available...
December 19, 2017: Cell Systems
Hisashi Noma, Kengo Nagashima, Kazushi Maruo, Masahiko Gosho, Toshi A Furukawa
In network meta-analyses that synthesize direct and indirect comparison evidence concerning multiple treatments, multivariate random effects models have been routinely used for addressing between-studies heterogeneities. Although their standard inference methods depend on large sample approximations (eg, restricted maximum likelihood estimation) for the number of trials synthesized, the numbers of trials are often moderate or small. In these situations, standard estimators cannot be expected to behave in accordance with asymptotic theory; in particular, confidence intervals cannot be assumed to exhibit their nominal coverage probabilities (also, the type I error probabilities of the corresponding tests cannot be retained)...
December 18, 2017: Statistics in Medicine
Kavitha Mukund, Shankar Subramaniam
Diseases affecting skeletal muscle exhibit considerable heterogeneity in intensity, etiology, phenotypic manifestation and gene expression. Systems biology approaches using network theory, allows for a holistic understanding of functional similarities amongst diseases. Here we propose a co-expression based, network theoretic approach to extract functional similarities from 20 heterogeneous diseases comprising of dystrophinopathies, inflammatory myopathies, neuromuscular, and muscle metabolic diseases. Utilizing this framework we identified seven closely associated disease clusters with 20 disease pairs exhibiting significant correlation (p < 0...
2017: Frontiers in Physiology
Lei Chen, Tao Liu, Xian Zhao
The anatomical therapeutic chemical (ATC) classification system is a widely accepted drug classification scheme. This system comprises five levels and includes several classes in each level. Drugs are classified into classes according to their therapeutic effects and characteristics. The first level includes 14 main classes. In this study, we proposed two network-based models to infer novel potential chemicals deemed to belong in the first level of ATC classification. To build these models, two large chemical networks were constructed using the chemical-chemical interaction information retrieved from the Search Tool for Interactions of Chemicals (STITCH)...
December 13, 2017: Biochimica et Biophysica Acta
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