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Gene network inference

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https://www.readbyqxmd.com/read/28334344/estimating-gene-regulatory-networks-with-pandar
#1
Daniel Schlauch, Joseph N Paulson, Albert Young, Kimberly Glass, John Quackenbush
PANDA (Passing Attributes betweenNetworks forData Assimilation) is a gene regulatory network inference method that begins with amodel of transcription factor-target gene interactions and usesmessage passing to update the network model given available transcriptomic and protein-protein interaction data. PANDA is used to estimate networks for each experimental group and the network models are then compared between groups to explore transcriptional processes that distinguish the groups. We present pandaR (bioconductor...
March 11, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28334268/an-algorithmic-perspective-of-de-novo-cis-regulatory-motif-finding-based-on-chip-seq-data
#2
Bingqiang Liu, Jinyu Yang, Yang Li, Adam McDermaid, Qin Ma
Transcription factors are proteins that bind to specific DNA sequences and play important roles in controlling the expression levels of their target genes. Hence, prediction of transcription factor binding sites (TFBSs) provides a solid foundation for inferring gene regulatory mechanisms and building regulatory networks for a genome. Chromatin immunoprecipitation sequencing (ChIP-seq) technology can generate large-scale experimental data for such protein-DNA interactions, providing an unprecedented opportunity to identify TFBSs (a...
March 8, 2017: Briefings in Bioinformatics
https://www.readbyqxmd.com/read/28333240/structure-of-the-transcriptional-regulatory-network-correlates-with-regulatory-divergence-in-drosophila
#3
Bing Yang, Patricia J Wittkopp
Transcriptional control of gene expression is regulated by biochemical interactions between cis-regulatory DNA sequences and trans-acting factors that form complex regulatory networks. Genetic changes affecting both cis- and trans-acting sequences in these networks have been shown to alter patterns of gene expression as well as higher-order organismal phenotypes. Here, we investigate how the structure of these regulatory networks relates to patterns of polymorphism and divergence in gene expression. To do this, we compared a transcriptional regulatory network inferred for Drosophila melanogaster to differences in gene regulation observed between two strains of D...
February 25, 2017: Molecular Biology and Evolution
https://www.readbyqxmd.com/read/28331847/learning-parsimonious-classification-rules-from-gene-expression-data-using-bayesian-networks-with-local-structure
#4
Jonathan Lyle Lustgarten, Jeya Balaji Balasubramanian, Shyam Visweswaran, Vanathi Gopalakrishnan
The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules...
March 2017: Data (Basel)
https://www.readbyqxmd.com/read/28327936/guidock-vnc-using-a-graphical-desktop-sharing-system-to-provide-a-browser-based-interface-for-containerized-software
#5
Varun Mittal, Ling-Hong Hung, Jayant Keswani, Daniel Kristiyanto, Sung Bong Lee, Ka Yee Yeung
Background: Software container technology such as Docker can be used to package and distribute bioinformatics workflows consisting of multiple software implementations and dependencies. However, Docker is a command line based tool and many bioinformatics pipelines consist of components that require a graphical user interface. Findings: We present a container tool called GUIdock-VNC that uses a graphical desktop sharing system to provide a browser-based interface for containerized software...
February 24, 2017: GigaScience
https://www.readbyqxmd.com/read/28326099/disease-risk-assessment-using-a-voronoi-based-network-analysis-of-genes-and-variants-scores
#6
Lin Chen, Gouri Mukerjee, Ruslan Dorfman, Seyed M Moghadas
Much effort has been devoted to assess disease risk based on large-scale protein-protein network and genotype-phenotype associations. However, the challenge of risk prediction for complex diseases remains unaddressed. Here, we propose a framework to quantify the risk based on a Voronoi tessellation network analysis, taking into account the disease association scores of both genes and variants. By integrating ClinVar, SNPnexus, and DISEASES databases, we introduce a gene-variant map that is based on the pairwise disease-associated gene-variant scores...
2017: Frontiers in Genetics
https://www.readbyqxmd.com/read/28325918/robust-analysis-of-fluxes-in-genome-scale-metabolic-pathways
#7
Michael MacGillivray, Amy Ko, Emily Gruber, Miranda Sawyer, Eivind Almaas, Allen Holder
Constraint-based optimization, such as flux balance analysis (FBA), has become a standard systems-biology computational method to study cellular metabolisms that are assumed to be in a steady state of optimal growth. The methods are based on optimization while assuming (i) equilibrium of a linear system of ordinary differential equations, and (ii) deterministic data. However, the steady-state assumption is biologically imperfect, and several key stoichiometric coefficients are experimentally inferred from situations of inherent variation...
March 21, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28322451/genome-wide-association-studies-with-proteomics-data-reveal-genes-important-for-synthesis-transport-and-packaging-of-globulins-in-legume-seeds
#8
Christine Le Signor, Delphine Aimé, Amandine Bordat, Maya Belghazi, Valérie Labas, Jérôme Gouzy, Nevin D Young, Jean-Marie Prosperi, Olivier Leprince, Richard D Thompson, Julia Buitink, Judith Burstin, Karine Gallardo
Improving nutritional seed quality is an important challenge in grain legume breeding. However, the genes controlling the differential accumulation of globulins, which are major contributors to seed nutritional value in legumes, remain largely unknown. We combined a search for protein quantity loci with genome-wide association studies on the abundance of 7S and 11S globulins in seeds of the model legume species Medicago truncatula. Identified genomic regions and genes carrying polymorphisms linked to globulin variations were then cross-compared with pea (Pisum sativum), leading to the identification of candidate genes for the regulation of globulin abundance in this crop...
March 21, 2017: New Phytologist
https://www.readbyqxmd.com/read/28301504/identification-of-marginal-causal-relationships-in-gene-networks-from-observational-and-interventional-expression-data
#9
Gilles Monneret, Florence Jaffrézic, Andrea Rau, Tatiana Zerjal, Grégory Nuel
Causal network inference is an important methodological challenge in biology as well as other areas of application. Although several causal network inference methods have been proposed in recent years, they are typically applicable for only a small number of genes, due to the large number of parameters to be estimated and the limited number of biological replicates available. In this work, we consider the specific case of transcriptomic studies made up of both observational and interventional data in which a single gene of biological interest is knocked out...
2017: PloS One
https://www.readbyqxmd.com/read/28301472/independent-introductions-and-admixtures-have-contributed-to-adaptation-of-european-maize-and-its-american-counterparts
#10
Jean-Tristan Brandenburg, Tristan Mary-Huard, Guillem Rigaill, Sarah J Hearne, Hélène Corti, Johann Joets, Clémentine Vitte, Alain Charcosset, Stéphane D Nicolas, Maud I Tenaillon
Through the local selection of landraces, humans have guided the adaptation of crops to a vast range of climatic and ecological conditions. This is particularly true of maize, which was domesticated in a restricted area of Mexico but now displays one of the broadest cultivated ranges worldwide. Here, we sequenced 67 genomes with an average sequencing depth of 18x to document routes of introduction, admixture and selective history of European maize and its American counterparts. To avoid the confounding effects of recent breeding, we targeted germplasm (lines) directly derived from landraces...
March 16, 2017: PLoS Genetics
https://www.readbyqxmd.com/read/28298218/systematic-identification-of-an-integrative-network-module-during-senescence-from-time-series-gene-expression
#11
Chihyun Park, So Jeong Yun, Sung Jin Ryu, Soyoung Lee, Young-Sam Lee, Youngmi Yoon, Sang Chul Park
BACKGROUND: Cellular senescence irreversibly arrests growth of human diploid cells. In addition, recent studies have indicated that senescence is a multi-step evolving process related to important complex biological processes. Most studies analyzed only the genes and their functions representing each senescence phase without considering gene-level interactions and continuously perturbed genes. It is necessary to reveal the genotypic mechanism inferred by affected genes and their interaction underlying the senescence process...
March 15, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28296635/dynamics-of-embryonic-stem-cell-differentiation-inferred-from-single-cell-transcriptomics-show-a-series-of-transitions-through-discrete-cell-states
#12
Sumin Jang, Sandeep Choubey, Leon Furchtgott, Ling-Nan Zou, Adele Doyle, Vilas Menon, Ethan B Loew, Anne-Rachel Krostag, Refugio A Martinez, Linda Madisen, Boaz P Levi, Sharad Ramanathan
The complexity of gene regulatory networks that lead multipotent cells to acquire different cell fates makes a quantitative understanding of differentiation challenging. Using a statistical framework to analyze single-cell transcriptomics data, we infer the gene expression dynamics of early mouse embryonic stem (mES) cell differentiation, uncovering discrete transitions across nine cell states. We validate the predicted transitions across discrete states using flow cytometry. Moreover, using live-cell microscopy, we show that individual cells undergo abrupt transitions from a naïve to primed pluripotent state...
March 15, 2017: ELife
https://www.readbyqxmd.com/read/28294630/peak-integrating-curated-and-noisy-prior-knowledge-in-gene-regulatory-network-inference
#13
Doaa Altarawy, Fatma-Elzahraa Eid, Lenwood S Heath
With abundance of biological data, computational prediction of gene regulatory networks (GRNs) from gene expression data has become more feasible. Although incorporating other prior knowledge (PK), along with gene expression data, greatly improves prediction accuracy, the overall accuracy is still low. PK in GRN inference can be categorized into noisy and curated. In noisy PK, relations between genes do not necessarily correspond to regulatory relations and are thus considered inaccurate by inference algorithms such as transcription factor binding and protein-protein interactions...
March 15, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28294287/learning-gene-regulatory-networks-from-next-generation-sequencing-data
#14
Bochao Jia, Suwa Xu, Guanghua Xiao, Vishal Lamba, Faming Liang
In recent years, next generation sequencing (NGS) has gradually replaced microarray as the major platform in measuring gene expressions. Compared to microarray, NGS has many advantages, such as less noise and higher throughput. However, the discreteness of NGS data also challenges the existing statistical methodology. In particular, there still lacks an appropriate statistical method for reconstructing gene regulatory networks using NGS data in the literature. The existing local Poisson graphical model method is not consistent and can only infer certain local structures of the network...
March 10, 2017: Biometrics
https://www.readbyqxmd.com/read/28292731/pathway-cross-talk-network-analysis-identifies-critical-pathways-in-neonatal-sepsis
#15
Yu-Xiu Meng, Quan-Hong Liu, Deng-Hong Chen, Ying Meng
BACKGROUND: Despite advances in neonatal care, sepsis remains a major cause of morbidity and mortality in neonates worldwide. Pathway cross-talk analysis might contribute to the inference of the driving forces in bacterial sepsis and facilitate a better understanding of underlying pathogenesis of neonatal sepsis. OBJECTIVE: This study aimed to explore the critical pathways associated with the progression of neonatal sepsis by the pathway cross-talk analysis. METHODS: By integrating neonatal transcriptome data with known pathway data and protein-protein interaction data, we systematically uncovered the disease pathway cross-talks and constructed a disease pathway cross-talk network for neonatal sepsis...
February 27, 2017: Computational Biology and Chemistry
https://www.readbyqxmd.com/read/28292312/comprehensive-discovery-of-subsample-gene-expression-components-by-information-explanation-therapeutic-implications-in-cancer
#16
Shirley Pepke, Greg Ver Steeg
BACKGROUND: De novo inference of clinically relevant gene function relationships from tumor RNA-seq remains a challenging task. Current methods typically either partition patient samples into a few subtypes or rely upon analysis of pairwise gene correlations that will miss some groups in noisy data. Leveraging higher dimensional information can be expected to increase the power to discern targetable pathways, but this is commonly thought to be an intractable computational problem. METHODS: In this work we adapt a recently developed machine learning algorithm for sensitive detection of complex gene relationships...
March 15, 2017: BMC Medical Genomics
https://www.readbyqxmd.com/read/28288905/bioinformatic-approaches-to-interrogating-vitamin-d-receptor-signaling
#17
Moray J Campbell
Bioinformatics applies unbiased approaches to develop statistically-robust insight into health and disease. At the global, or "20,000 foot" view bioinformatic analyses of vitamin D receptor (NR1I1/VDR) signaling can measure where the VDR gene or protein exerts a genome-wide significant impact on biology; VDR is significantly implicated in bone biology and immune systems, but not in cancer. With a more VDR-centric, or "2000 foot" view, bioinformatic approaches can interrogate events downstream of VDR activity...
March 10, 2017: Molecular and Cellular Endocrinology
https://www.readbyqxmd.com/read/28288164/bayesian-model-of-signal-rewiring-reveals-mechanisms-of-gene-dysregulation-in-acquired-drug-resistance-in-breast-cancer
#18
A K M Azad, Alfons Lawen, Jonathan M Keith
Small molecule inhibitors, such as lapatinib, are effective against breast cancer in clinical trials, but tumor cells ultimately acquire resistance to the drug. Maintaining sensitization to drug action is essential for durable growth inhibition. Recently, adaptive reprogramming of signaling circuitry has been identified as a major cause of acquired resistance. We developed a computational framework using a Bayesian statistical approach to model signal rewiring in acquired resistance. We used the p1-model to infer potential aberrant gene-pairs with differential posterior probabilities of appearing in resistant-vs-parental networks...
2017: PloS One
https://www.readbyqxmd.com/read/28274758/gfd-net-a-novel-semantic-similarity-methodology-for-the-analysis-of-gene-networks
#19
Juan J Díaz-Montaña, Norberto Díaz-Díaz, Francisco Gómez-Vela
Since the popularization of biological network inference methods, it has become crucial to create methods to validate the resulting models. Here we present GFD-Net, the first methodology that applies the concept of semantic similarity to gene network analysis. GFD-Net combines the concept of semantic similarity with the use of gene network topology to analyze the functional dissimilarity of gene networks based on Gene Ontology (GO). The main innovation of GFD-Net lies in the way that semantic similarity is used to analyze gene networks taking into account the network topology...
March 5, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28270809/functional-diversity-of-transcriptional-regulators-in-the-cyanobacterium-synechocystis-sp-pcc-6803
#20
Mengliang Shi, Xiaoqing Zhang, Guangsheng Pei, Lei Chen, Weiwen Zhang
Functions of transcriptional regulators (TRs) are still poorly understood in the model cyanobacterium Synechocystis sp. PCC 6803. To address the issue, we constructed knockout mutants for 32 putative TR-encoding genes of Synechocystis, and comparatively analyzed their phenotypes under autotrophic growth condition and metabolic profiles using liquid chromatography-mass spectrometry-based metabolomics. The results showed that only four mutants of TR genes, sll1872 (lytR), slr0741 (phoU), slr0395 (ntcB), and slr1871 (pirR), showed differential growth patterns in BG11 medium when compared with the wild type; however, in spite of no growth difference observed for the remaining TR mutants, metabolomic profiling showed that they were different at the metabolite level, suggesting significant functional diversity of TRs in Synechocystis...
2017: Frontiers in Microbiology
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