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Gene network inference

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https://www.readbyqxmd.com/read/28208380/inferring-hidden-states-in-langevin-dynamics-on-large-networks-average-case-performance
#1
B Bravi, M Opper, P Sollich
We present average performance results for dynamical inference problems in large networks, where a set of nodes is hidden while the time trajectories of the others are observed. Examples of this scenario can occur in signal transduction and gene regulation networks. We focus on the linear stochastic dynamics of continuous variables interacting via random Gaussian couplings of generic symmetry. We analyze the inference error, given by the variance of the posterior distribution over hidden paths, in the thermodynamic limit and as a function of the system parameters and the ratio α between the number of hidden and observed nodes...
January 2017: Physical Review. E
https://www.readbyqxmd.com/read/28200075/an-approach-to-infer-putative-disease-specific-mechanisms-using-neighboring-gene-networks
#2
Sahar Ansari, Michele Donato, Nafiseh Saberian, Sorin Draghici
No abstract text is available yet for this article.
February 15, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28197408/module-anchored-network-inference-a-sequential-module-based-approach-to-novel-gene-network-construction-from-genomic-expression-data-on-human-disease-mechanism
#3
Annamalai Muthiah, Susanna R Keller, Jae K Lee
Different computational approaches have been examined and compared for inferring network relationships from time-series genomic data on human disease mechanisms under the recent Dialogue on Reverse Engineering Assessment and Methods (DREAM) challenge. Many of these approaches infer all possible relationships among all candidate genes, often resulting in extremely crowded candidate network relationships with many more False Positives than True Positives. To overcome this limitation, we introduce a novel approach, Module Anchored Network Inference (MANI), that constructs networks by analyzing sequentially small adjacent building blocks (modules)...
2017: International Journal of Genomics
https://www.readbyqxmd.com/read/28192619/genomic-signatures-of-adaptation-to-wine-biological-aging-conditions%C3%A2-in-biofilm-forming-flor-yeasts
#4
A L Coi, F Bigey, S Mallet, S Marsit, G Zara, P Gladieux, V Galeote, M Budroni, S Dequin, J L Legras
The molecular and evolutionary processes underlying fungal domestication remain largely unknown despite the importance of fungi to bioindustry and for comparative adaptation genomics in eukaryotes. Wine fermentation and biological aging are performed by strains of S. cerevisiae with, respectively, pelagic fermentative growth on glucose, and biofilm aerobic growth utilizing ethanol. Here, we use environmental samples of wine and flor yeasts to investigate the genomic basis of yeast adaptation to contrasted anthropogenic environments...
February 13, 2017: Molecular Ecology
https://www.readbyqxmd.com/read/28187708/incorporating-prior-biological-knowledge-for-network-based-differential-gene-expression-analysis-using-differentially-weighted-graphical-lasso
#5
Yiming Zuo, Yi Cui, Guoqiang Yu, Ruijiang Li, Habtom W Ressom
BACKGROUND: Conventional differential gene expression analysis by methods such as student's t-test, SAM, and Empirical Bayes often searches for statistically significant genes without considering the interactions among them. Network-based approaches provide a natural way to study these interactions and to investigate the rewiring interactions in disease versus control groups. In this paper, we apply weighted graphical LASSO (wgLASSO) algorithm to integrate a data-driven network model with prior biological knowledge (i...
February 10, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28186904/a-combined-pls-and-negative-binomial-regression-model-for-inferring-association-networks-from-next-generation-sequencing-count-data
#6
Maiju Pesonen, Jaakko Nevalainen, Steven Potter, Somnath Datta, Susmita Datta
A major challenge of genomics data is to detect interactions displaying functional associations from large-scale observations. In this study, a new cPLS-algorithm combining partial least squares approach with negative binomial regression is suggested to reconstruct a genomic association network for high-dimensional next-generation sequencing count data. The suggested approach is applicable to the raw counts data, without requiring any further pre-processing steps. In the settings investigated, the cPLS-algorithm outperformed the two widely used comparative methods, graphical lasso and weighted correlation network analysis...
February 7, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28185572/in-the-light-of-deep-coalescence-revisiting-trees-within-networks
#7
Jiafan Zhu, Yun Yu, Luay Nakhleh
BACKGROUND: Phylogenetic networks model reticulate evolutionary histories. The last two decades have seen an increased interest in establishing mathematical results and developing computational methods for inferring and analyzing these networks. A salient concept underlying a great majority of these developments has been the notion that a network displays a set of trees and those trees can be used to infer, analyze, and study the network. RESULTS: In this paper, we show that in the presence of coalescence effects, the set of displayed trees is not sufficient to capture the network...
November 11, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/28183358/genetic-diversity-and-population-structure-of-the-primary-malaria-vector-anopheles-sinensis-diptera-culicidae-in-china-inferred-by-cox1-gene
#8
Xinyu Feng, Libin Huang, Lin Lin, Manni Yang, Yajun Ma
BACKGROUND: Anopheles sinensis is a primary vector for Plasmodium vivax malaria in most regions of China. A comprehensive understanding of genetic variation and structure of the mosquito would be of benefit to the vector control and in a further attempt to contribute to malaria elimination in China. However, there is only inadequate population genetic data pertaining to An. sinensis currently. METHODS: Genetic variations and structure among populations of An. sinensis was examined and analyzed based on the nucleotide sequences of a 662 nt variable region of the mitochondrial cox1 gene among 15 populations from 20 collection sites in China...
February 10, 2017: Parasites & Vectors
https://www.readbyqxmd.com/read/28178334/a-novel-mutual-information-based-boolean-network-inference-method-from-time-series-gene-expression-data
#9
Shohag Barman, Yung-Keun Kwon
BACKGROUND: Inferring a gene regulatory network from time-series gene expression data in systems biology is a challenging problem. Many methods have been suggested, most of which have a scalability limitation due to the combinatorial cost of searching a regulatory set of genes. In addition, they have focused on the accurate inference of a network structure only. Therefore, there is a pressing need to develop a network inference method to search regulatory genes efficiently and to predict the network dynamics accurately...
2017: PloS One
https://www.readbyqxmd.com/read/28174237/single-cell-transcriptomics-of-the-human-placenta-inferring-the-cell-communication-network-of-the-maternal-fetal-interface
#10
Mihaela Pavličev, Günter P Wagner, Arun Rajendra Chavan, Kathryn Owens, Jamie Maziarz, Caitlin Dunn-Fletcher, Suhas G Kallapur, Louis Muglia, Helen Jones
Organismal function is, to a great extent, determined by interactions among their fundamental building blocks, the cells. In this work, we studied the cell-cell interactome of fetal placental trophoblast cells and maternal endometrial stromal cells, using single-cell transcriptomics. The placental interface mediates the interaction between two semiallogenic individuals, the mother and the fetus, and is thus the epitome of cell interactions. To study these, we inferred the cell-cell interactome by assessing the gene expression of receptor-ligand pairs across cell types...
February 7, 2017: Genome Research
https://www.readbyqxmd.com/read/28173765/selection-on-the-mitochondrial-atp-synthase-6-and-the-nadh-dehydrogenase-2-genes-in-hares-lepus-capensis-l-1758-from-a-steep-ecological-gradient-in-north-africa
#11
Hichem Ben Slimen, Helmut Schaschl, Felix Knauer, Franz Suchentrunk
BACKGROUND: Recent studies of selection on mitochondrial (mt) OXPHOS genes suggest adaptation due mainly to environmental variation. In this context, Tunisian hares that display several external phenotypes with phylogenetically rather homogenous gene pool and shallow population structure provide a good precondition to detect positive selection on mt genes related to environmental/climatic variation, specifically ambient temperature and precipitation. RESULTS: We used codon-based methods along with population genetic data to test for positive selection on ATPase synthase 6 (ATP6) and NADH dehydrogenase 2 (ND2) of cape hares (Lepus capensis) collected along a steep ecological gradient in Tunisia...
February 7, 2017: BMC Evolutionary Biology
https://www.readbyqxmd.com/read/28166542/expectation-propagation-for-large-scale-bayesian-inference-of-non-linear-molecular-networks-from-perturbation-data
#12
Zahra Narimani, Hamid Beigy, Ashar Ahmad, Ali Masoudi-Nejad, Holger Fröhlich
Inferring the structure of molecular networks from time series protein or gene expression data provides valuable information about the complex biological processes of the cell. Causal network structure inference has been approached using different methods in the past. Most causal network inference techniques, such as Dynamic Bayesian Networks and ordinary differential equations, are limited by their computational complexity and thus make large scale inference infeasible. This is specifically true if a Bayesian framework is applied in order to deal with the unavoidable uncertainty about the correct model...
2017: PloS One
https://www.readbyqxmd.com/read/28158291/recursive-random-forest-algorithm-for-constructing-multilayered-hierarchical-gene-regulatory-networks-that-govern-biological-pathways
#13
Wenping Deng, Kui Zhang, Victor Busov, Hairong Wei
BACKGROUND: Present knowledge indicates a multilayered hierarchical gene regulatory network (ML-hGRN) often operates above a biological pathway. Although the ML-hGRN is very important for understanding how a pathway is regulated, there is almost no computational algorithm for directly constructing ML-hGRNs. RESULTS: A backward elimination random forest (BWERF) algorithm was developed for constructing the ML-hGRN operating above a biological pathway. For each pathway gene, the BWERF used a random forest model to calculate the importance values of all transcription factors (TFs) to this pathway gene recursively with a portion (e...
2017: PloS One
https://www.readbyqxmd.com/read/28155637/cmip-a-software-package-capable-of-reconstructing-genome-wide-regulatory-networks-using-gene-expression-data
#14
Guangyong Zheng, Yaochen Xu, Xiujun Zhang, Zhi-Ping Liu, Zhuo Wang, Luonan Chen, Xin-Guang Zhu
BACKGROUND: A gene regulatory network (GRN) represents interactions of genes inside a cell or tissue, in which vertexes and edges stand for genes and their regulatory interactions respectively. Reconstruction of gene regulatory networks, in particular, genome-scale networks, is essential for comparative exploration of different species and mechanistic investigation of biological processes. Currently, most of network inference methods are computationally intensive, which are usually effective for small-scale tasks (e...
December 23, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/28154557/robust-inference-of-genetic-exchange-communities-from-microbial-genomes-using-tf-idf
#15
Yingnan Cong, Yao-Ban Chan, Charles A Phillips, Michael A Langston, Mark A Ragan
Bacteria and archaea can exchange genetic material across lineages through processes of lateral genetic transfer (LGT). Collectively, these exchange relationships can be modeled as a network and analyzed using concepts from graph theory. In particular, densely connected regions within an LGT network have been defined as genetic exchange communities (GECs). However, it has been problematic to construct networks in which edges solely represent LGT. Here we apply term frequency-inverse document frequency (TF-IDF), an alignment-free method originating from document analysis, to infer regions of lateral origin in bacterial genomes...
2017: Frontiers in Microbiology
https://www.readbyqxmd.com/read/28145456/enhancing-gene-regulatory-network-inference-through-data-integration-with-markov-random-fields
#16
Michael Banf, Seung Y Rhee
A gene regulatory network links transcription factors to their target genes and represents a map of transcriptional regulation. Much progress has been made in deciphering gene regulatory networks computationally. However, gene regulatory network inference for most eukaryotic organisms remain challenging. To improve the accuracy of gene regulatory network inference and facilitate candidate selection for experimentation, we developed an algorithm called GRACE (Gene Regulatory network inference ACcuracy Enhancement)...
February 1, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28133490/inference-of-gene-regulatory-networks-using-bayesian-nonparametric-regression-and-topology-information
#17
Yue Fan, Xiao Wang, Qinke Peng
Gene regulatory networks (GRNs) play an important role in cellular systems and are important for understanding biological processes. Many algorithms have been developed to infer the GRNs. However, most algorithms only pay attention to the gene expression data but do not consider the topology information in their inference process, while incorporating this information can partially compensate for the lack of reliable expression data. Here we develop a Bayesian group lasso with spike and slab priors to perform gene selection and estimation for nonparametric models...
2017: Computational and Mathematical Methods in Medicine
https://www.readbyqxmd.com/read/28127303/reverse-engineering-gene-regulatory-networks-from-measurement-with-missing-values
#18
Oyetunji E Ogundijo, Abdulkadir Elmas, Xiaodong Wang
BACKGROUND: Gene expression time series data are usually in the form of high-dimensional arrays. Unfortunately, the data may sometimes contain missing values: for either the expression values of some genes at some time points or the entire expression values of a single time point or some sets of consecutive time points. This significantly affects the performance of many algorithms for gene expression analysis that take as an input, the complete matrix of gene expression measurement. For instance, previous works have shown that gene regulatory interactions can be estimated from the complete matrix of gene expression measurement...
December 2016: EURASIP Journal on Bioinformatics & Systems Biology
https://www.readbyqxmd.com/read/28118365/medici-mining-essentiality-data-to-identify-critical-interactions-for-cancer-drug-target-discovery-and-development
#19
Sahar Harati, Lee A D Cooper, Josue D Moran, Felipe O Giuste, Yuhong Du, Andrei A Ivanov, Margaret A Johns, Fadlo R Khuri, Haian Fu, Carlos S Moreno
Protein-protein interactions (PPIs) mediate the transmission and regulation of oncogenic signals that are essential to cellular proliferation and survival, and thus represent potential targets for anti-cancer therapeutic discovery. Despite their significance, there is no method to experimentally disrupt and interrogate the essentiality of individual endogenous PPIs. The ability to computationally predict or infer PPI essentiality would help prioritize PPIs for drug discovery and help advance understanding of cancer biology...
2017: PloS One
https://www.readbyqxmd.com/read/28117655/gsnfs-gene-subnetwork-biomarker-identification-of-lung-cancer-expression-data
#20
Narumol Doungpan, Worrawat Engchuan, Jonathan H Chan, Asawin Meechai
BACKGROUND: Gene expression has been used to identify disease gene biomarkers, but there are ongoing challenges. Single gene or gene-set biomarkers are inadequate to provide sufficient understanding of complex disease mechanisms and the relationship among those genes. Network-based methods have thus been considered for inferring the interaction within a group of genes to further study the disease mechanism. Recently, the Gene-Network-based Feature Set (GNFS), which is capable of handling case-control and multiclass expression for gene biomarker identification, has been proposed, partly taking into account of network topology...
December 5, 2016: BMC Medical Genomics
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