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https://www.readbyqxmd.com/read/28443230/prediction-of-optimal-gene-functions-for-osteosarcoma-using-network-based-guilt-by-association-method-based-on-gene-oncology-and-microarray-profile
#1
Xinrang Chen
In the current study, we planned to predict the optimal gene functions for osteosarcoma (OS) by integrating network-based method with guilt by association (GBA) principle (called as network-based gene function inference approach) based on gene oncology (GO) data and gene expression profile. To begin with, differentially expressed genes (DEGs) were extracted using linear models for microarray data (LIMMA) package. Then, construction of differential co-expression network (DCN) relying on DEGs was implemented, and sub-DCN was identified using Spearman correlation coefficient (SCC)...
June 2017: Journal of Bone Oncology
https://www.readbyqxmd.com/read/28440122/effects-of-low-dose-ionizing-radiation-on-dna-damage-caused-pathways-by-reverse-phase-protein-array-and-bayesian-networks
#2
Dong-Chul Kim, Mingon Kang, Ashis Biswas, Chin-Rang Yang, Xiaoyu Wang, Jean X Gao
Ionizing radiation (IR) causing damages to Deoxyribonucleic acid (DNA) constitutes a broad range of base damage and double strand break, and thereby, it induces the operation of relevant signaling pathways such as DNA repair, cell cycle control, and cell apoptosis. The goal of this paper is to study how the exposure to low dose radiation affects the human body by observing the signaling pathway associated with Ataxia Telangiectasia mutated (ATM) using Reverse-Phase Protein Array (RPPA) and isogenic human Ataxia Telangiectasia (A-T) cells under different amounts and durations of IR exposure...
April 2017: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/28439014/brain-networks-for-confidence-weighting-and-hierarchical-inference-during-probabilistic-learning
#3
Florent Meyniel, Stanislas Dehaene
Learning is difficult when the world fluctuates randomly and ceaselessly. Classical learning algorithms, such as the delta rule with constant learning rate, are not optimal. Mathematically, the optimal learning rule requires weighting prior knowledge and incoming evidence according to their respective reliabilities. This "confidence weighting" implies the maintenance of an accurate estimate of the reliability of what has been learned. Here, using fMRI and an ideal-observer analysis, we demonstrate that the brain's learning algorithm relies on confidence weighting...
April 24, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28436883/a-bipartite-network-and-resource-transfer-based-approach-to-infer-lncrna-environmental-factor-associations
#4
Jie Zhou, Yuan-Yuan Shi
Phenotypes and diseases are often determined by the complex interactions between genetic factors and environmental factors (EFs). However, compared with protein-coding genes and microRNAs, there is a paucity of computational methods for understanding the associations between long non-coding RNAs (lncRNAs) and EFs. In this study, we focused on the associations between lncRNA and EFs. By using the common miRNA partners of any pair of lncRNA and EF, based on the competing endogenous RNA (ceRNA) hypothesis and the technique of resources transfer within the experimentally-supported lncRNA-miRNA and miRNA-EF association bipartite networks, we propose an algorithm for predicting new lncRNA-EF associations...
April 18, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28432214/a-microrna-mrna-expression-network-during-oral-siphon-regeneration-in-ciona
#5
Elijah J Spina, Elmer Guzman, Hongjun Zhou, Kenneth S Kosik, William C Smith
Here we present a parallel study of mRNA and microRNA expression during oral siphon (OS) regeneration in Ciona robusta, and the derived network of their interactions. In the process of identifying 248 mRNAs and 15 microRNAs as differentially expressed (DE), we also identified 57 novel microRNAs, several of which are among the most highly DE. Analysis of functional categories identified enriched transcripts related to stress responses and apoptosis at the wound healing stage, signaling pathways including Wnt and TGF-β during early regrowth, and negative regulation of extracellular proteases in late stage regeneration...
April 21, 2017: Development
https://www.readbyqxmd.com/read/28430779/a-coevolution-analysis-for-identifying-protein-protein-interactions-by-fourier-transform
#6
Changchuan Yin, Stephen S-T Yau
Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees...
2017: PloS One
https://www.readbyqxmd.com/read/28426211/dry-particulate-nitrate-deposition-in-china
#7
Lei Liu, Xiuying Zhang, Yan Zhang, Wen xU, Xuejun Liu, Xiaoming Zhang, Junlan Feng, Xinrui Chen, Yuehan Zhang, Xuehe Lu, Shanqian Wang, Wuting Zhang, Limin Zhao
A limited number of ground measurements of dry particulate nitrate deposition (NO3-) makes it difficult and challenging to fully know the status of the spatial and temporal variations of dry NO3- depositions over China. This study tries to expand the ground measurements of NO3- concentrations at monitoring sites to a national scale, based on the Ozone Monitoring Instrument (OMI) NO2 columns, NO2 profiles from an atmospheric chemistry transport model (Model for Ozone and Related chemical Tracers, version 4, MOZART-4) and monitor-based sources, and then estimates the NO3- depositions on a regional scale based on an inferred model...
April 20, 2017: Environmental Science & Technology
https://www.readbyqxmd.com/read/28419682/game-theoretical-mapping-of-causal-interactions-underlying-visuo-spatial-attention-in-the-human-brain-based-on-stroke-lesions
#8
Monica N Toba, Melissa Zavaglia, Federica Rastelli, Romain Valabrégue, Pascale Pradat-Diehl, Antoni Valero-Cabré, Claus C Hilgetag
Anatomical studies conducted in neurological conditions have developed our understanding of the causal relationships between brain lesions and their clinical consequences. The analysis of lesion patterns extended across brain networks has been particularly useful in offering new insights on brain-behavior relationships. Here we applied multiperturbation Shapley value Analysis (MSA), a multivariate method based on coalitional game theory inferring causal regional contributions to specific behavioral outcomes from the characteristic functional deficits after stroke lesions...
April 17, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28419235/a-bayesian-group-sparse-multi-task-regression-model-for-imaging-genetics
#9
Keelin Greenlaw, Elena Szefer, Jinko Graham, Mary Lesperance, Farouk S Nathoo
Motivation: Recent advances in technology for brain imaging and high-throughput genotyping have motivated studies examining the influence of genetic variation on brain structure. Wang et al. (Bioinformatics, 2012) have developed an approach for the analysis of imaging genomic studies using penalized multi-task regression with regularization based on a novel group l2,1-norm penalty which encourages structured sparsity at both the gene level and SNP level. While incorporating a number of useful features, the proposed method only furnishes a point estimate of the regression coefficients; techniques for conducting statistical inference are not provided...
April 13, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28418398/intranasal-oxytocin-enhances-intrinsic-corticostriatal-functional-connectivity-in-women
#10
R A I Bethlehem, M V Lombardo, M-C Lai, B Auyeung, S K Crockford, J Deakin, S Soubramanian, A Sule, P Kundu, V Voon, S Baron-Cohen
Oxytocin may influence various human behaviors and the connectivity across subcortical and cortical networks. Previous oxytocin studies are male biased and often constrained by task-based inferences. Here, we investigate the impact of oxytocin on resting-state connectivity between subcortical and cortical networks in women. We collected resting-state functional magnetic resonance imaging (fMRI) data on 26 typically developing women 40 min following intranasal oxytocin administration using a double-blind placebo-controlled crossover design...
April 18, 2017: Translational Psychiatry
https://www.readbyqxmd.com/read/28415237/latent-geometry-of-bipartite-networks
#11
Maksim Kitsak, Fragkiskos Papadopoulos, Dmitri Krioukov
Despite the abundance of bipartite networked systems, their organizing principles are less studied compared to unipartite networks. Bipartite networks are often analyzed after projecting them onto one of the two sets of nodes. As a result of the projection, nodes of the same set are linked together if they have at least one neighbor in common in the bipartite network. Even though these projections allow one to study bipartite networks using tools developed for unipartite networks, one-mode projections lead to significant loss of information and artificial inflation of the projected network with fully connected subgraphs...
March 2017: Physical Review. E
https://www.readbyqxmd.com/read/28413725/trypanosoma-cruzi-reservoir-triatomine-vector-co-occurrence-networks-reveal-meta-community-effects-by-synanthropic-mammals-on-geographic-dispersal
#12
Carlos N Ibarra-Cerdeña, Leopoldo Valiente-Banuet, Víctor Sánchez-Cordero, Christopher R Stephens, Janine M Ramsey
Contemporary patterns of land use and global climate change are modifying regional pools of parasite host species. The impact of host community changes on human disease risk, however, is difficult to assess due to a lack of information about zoonotic parasite host assemblages. We have used a recently developed method to infer parasite-host interactions for Chagas Disease (CD) from vector-host co-occurrence networks. Vector-host networks were constructed to analyze topological characteristics of the network and ecological traits of species' nodes, which could provide information regarding parasite regional dispersal in Mexico...
2017: PeerJ
https://www.readbyqxmd.com/read/28413566/a-hierarchical-predictive-coding-model-of-object-recognition-in-natural-images
#13
M W Spratling
Predictive coding has been proposed as a model of the hierarchical perceptual inference process performed in the cortex. However, results demonstrating that predictive coding is capable of performing the complex inference required to recognise objects in natural images have not previously been presented. This article proposes a hierarchical neural network based on predictive coding for performing visual object recognition. This network is applied to the tasks of categorising hand-written digits, identifying faces, and locating cars in images of street scenes...
2017: Cognitive Computation
https://www.readbyqxmd.com/read/28408966/gene-network-reconstruction-using-global-local-shrinkage-priors
#14
Gwenaël G R Leday, Mathisca C M de Gunst, Gino B Kpogbezan, Aad W van der Vaart, Wessel N van Wieringen, Mark A van de Wiel
Reconstructing a gene network from high-throughput molecular data is an important but challenging task, as the number of parameters to estimate easily is much larger than the sample size. A conventional remedy is to regularize or penalize the model likelihood. In network models, this is often done locally in the neighbourhood of each node or gene. However, estimation of the many regularization parameters is often difficult and can result in large statistical uncertainties. In this paper we propose to combine local regularization with global shrinkage of the regularization parameters to borrow strength between genes and improve inference...
March 2017: Annals of Applied Statistics
https://www.readbyqxmd.com/read/28408281/comparison-of-ann-mlp-anfis-svm-and-rf-models-for-the-online-classification-of-heating-value-of-burning-municipal-solid-waste-in-circulating-fluidized-bed-incinerators
#15
Haihui You, Zengyi Ma, Yijun Tang, Yuelan Wang, Jianhua Yan, Mingjiang Ni, Kefa Cen, Qunxing Huang
The heating values, particularly lower heating values of burning municipal solid waste are critically important parameters in operating circulating fluidized bed incineration systems. However, the heating values change widely and frequently, while there is no reliable real-time instrument to measure heating values in the process of incinerating municipal solid waste. A rapid, cost-effective, and comparative methodology was proposed to evaluate the heating values of burning MSW online based on prior knowledge, expert experience, and data-mining techniques...
April 10, 2017: Waste Management
https://www.readbyqxmd.com/read/28407042/incorporating-prior-information-into-differential-network-analysis-using-nonparanormal-graphical-models
#16
Xiao-Fei Zhang, Le Ou-Yang, Hong Yan
Motivation: Understanding how gene regulatory networks change under different cellular states is important for revealing insights into network dynamics. Gaussian graphical models, which assume that the data follow a joint normal distribution, have been used recently to infer differential networks. However, the distributions of the omics data are nonnormal in general. Furthermore, althoughmuch biological knowledge (or prior information) has been accumulated, most existing methods ignore the valuable prior information...
April 12, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28393396/an-empirical-bayes-approach-to-network-recovery-using-external-knowledge
#17
Gino B Kpogbezan, Aad W van der Vaart, Wessel N van Wieringen, Gwenaël G R Leday, Mark A van de Wiel
Reconstruction of a high-dimensional network may benefit substantially from the inclusion of prior knowledge on the network topology. In the case of gene interaction networks such knowledge may come for instance from pathway repositories like KEGG, or be inferred from data of a pilot study. The Bayesian framework provides a natural means of including such prior knowledge. Based on a Bayesian Simultaneous Equation Model, we develop an appealing Empirical Bayes (EB) procedure that automatically assesses the agreement of the used prior knowledge with the data at hand...
April 10, 2017: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/28389083/node-based-differential-network-analysis-in-genomics
#18
Xiao-Fei Zhang, Le Ou-Yang, Hong Yan
Gene dependency networks often undergo changes in response to different conditions. Understanding how these networks change across two conditions is an important task in genomics research. Most previous differential network analysis approaches assume that the difference between two condition-specific networks is driven by individual edges. Thus, they may fail in detecting key players which might represent important genes whose mutations drive the change of network. In this work, we develop a node-based differential network analysis (N-DNA) model to directly estimate the differential network that is driven by certain hub nodes...
April 4, 2017: Computational Biology and Chemistry
https://www.readbyqxmd.com/read/28381545/drug-resistance-mechanisms-in-colorectal-cancer-dissected-with-cell-type-specific-dynamic-logic-models
#19
Federica Eduati, Victoria Doldàn-Martelli, Bertram Klinger, Thomas Cokelaer, Anja Sieber, Fiona Kogera, Mathurin Dorel, Mathew J Garnett, Nils Blüthgen, Julio Saez-Rodriguez
Genomic features are used as biomarkers of sensitivity to kinase inhibitors used widely to treat human cancer, but effective patient stratification based on these principles remains limited in impact. Insofar as kinase inhibitors interfere with signaling dynamics, and, in turn, signaling dynamics affects inhibitor responses, we investigated associations in this study between cell-specific dynamic signaling pathways and drug sensitivity. Specifically, we measured 14 phosphoproteins under 43 different perturbed conditions (combinations of 5 stimuli and 7 inhibitors) in 14 colorectal cancer cell lines, building cell line-specific dynamic logic models of underlying signaling networks...
April 5, 2017: Cancer Research
https://www.readbyqxmd.com/read/28380048/a-study-of-the-transferability-of-influenza-case-detection-systems-between-two-large-healthcare-systems
#20
Ye Ye, Michael M Wagner, Gregory F Cooper, Jeffrey P Ferraro, Howard Su, Per H Gesteland, Peter J Haug, Nicholas E Millett, John M Aronis, Andrew J Nowalk, Victor M Ruiz, Arturo López Pineda, Lingyun Shi, Rudy Van Bree, Thomas Ginter, Fuchiang Tsui
OBJECTIVES: This study evaluates the accuracy and transferability of Bayesian case detection systems (BCD) that use clinical notes from emergency department (ED) to detect influenza cases. METHODS: A BCD uses natural language processing (NLP) to infer the presence or absence of clinical findings from ED notes, which are fed into a Bayesain network classifier (BN) to infer patients' diagnoses. We developed BCDs at the University of Pittsburgh Medical Center (BCDUPMC) and Intermountain Healthcare in Utah (BCDIH)...
2017: PloS One
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