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Gene network inference

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https://www.readbyqxmd.com/read/29145845/network-pharmacological-mechanisms-of-vernonia-anthelmintica-l-in-the-treatment-of-vitiligo-isorhamnetin-induction-of-melanogenesis-via-up-regulation-of-melanin-biosynthetic-genes
#1
Ji Ye Wang, Hong Chen, Yin Yin Wang, Xiao Qin Wang, Han Ying Chen, Mei Zhang, Yun Tang, Bo Zhang
BACKGROUND: Vitiligo is a long-term skin disease characterized by the loss of pigment in the skin. The current therapeutic approaches are limited. Although the anti-vitiligo mechanisms of Vernonia anthelmintica (L.) remain ambiguous, the herb has been broadly used in Uyghur hospitals to treat vitiligo. The overall objective of the present study aims to identify the potential lead compounds from Vernonia anthelmintica (L.) in the treatment of vitiligo via an oral route as well as the melanogenic mechanisms in the systematic approaches in silico of admetSAR and substructure-drug-target network-based inference (SDTNBI)...
November 16, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/29145803/unraveling-the-evolution-and-coevolution-of-small-regulatory-rnas-and-coding-genes-in-listeria
#2
Franck Cerutti, Ludovic Mallet, Anaïs Painset, Claire Hoede, Annick Moisan, Christophe Bécavin, Mélodie Duval, Olivier Dussurget, Pascale Cossart, Christine Gaspin, Hélène Chiapello
BACKGROUND: Small regulatory RNAs (sRNAs) are widely found in bacteria and play key roles in many important physiological and adaptation processes. Studying their evolution and screening for events of coevolution with other genomic features is a powerful way to better understand their origin and assess a common functional or adaptive relationship between them. However, evolution and coevolution of sRNAs with coding genes have been sparsely investigated in bacterial pathogens. RESULTS: We designed a robust and generic phylogenomics approach that detects correlated evolution between sRNAs and protein-coding genes using their observed and inferred patterns of presence-absence in a set of annotated genomes...
November 16, 2017: BMC Genomics
https://www.readbyqxmd.com/read/29145449/estimation-of-the-proteomic-cancer-co-expression-sub-networks-by-using-association-estimators
#3
Cihat Erdoğan, Zeyneb Kurt, Banu Diri
In this study, the association estimators, which have significant influences on the gene network inference methods and used for determining the molecular interactions, were examined within the co-expression network inference concept. By using the proteomic data from five different cancer types, the hub genes/proteins within the disease-associated gene-gene/protein-protein interaction sub networks were identified. Proteomic data from various cancer types is collected from The Cancer Proteome Atlas (TCPA). Correlation and mutual information (MI) based nine association estimators that are commonly used in the literature, were compared in this study...
2017: PloS One
https://www.readbyqxmd.com/read/29142227/population-genetic-structure-of-the-land-snail-camaena-cicatricosa-stylommatophora-camaenidae-in-china-inferred-from-mitochondrial-genes-and-its2-sequences
#4
Weichuan Zhou, Haifang Yang, Hongli Ding, Shanping Yang, Junhong Lin, Pei Wang
The phylogeographic structure of the land snail Camaena cicatricosa was analyzed in this study based on mitochondrial gene (COI and 16srRNA, mt DNA) and internal transcribed spacer (ITS2) sequences in 347 individuals. This snail is the vector of the zoonotic food-borne parasite Angiostrongylus cantonensis and one of the main harmful snails distributed exclusively in China. The results revealed significant fixation indices of genetic differentiation and high gene flow between most populations except several populations...
November 15, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29125126/improving-grn-re-construction-by-mining-hidden-regulatory-signals
#5
Ming Shi, Weiming Shen, Yanwen Chong, Hong-Qiang Wang
Inferring gene regulatory networks (GRNs) from gene expression data is an important but challenging issue in systems biology. Here, the authors propose a dictionary learning-based approach that aims to infer GRNs by globally mining regulatory signals, known or latent. Gene expression is often regulated by various regulatory factors, some of which are observed and some of which are latent. The authors assume that all regulators are unknown for a target gene and the expression of the target gene can be mapped into a regulatory space spanned by all the regulators...
December 2017: IET Systems Biology
https://www.readbyqxmd.com/read/29122012/drug-target-ontology-to-classify-and-integrate-drug-discovery-data
#6
Yu Lin, Saurabh Mehta, Hande Küçük-McGinty, John Paul Turner, Dusica Vidovic, Michele Forlin, Amar Koleti, Dac-Trung Nguyen, Lars Juhl Jensen, Rajarshi Guha, Stephen L Mathias, Oleg Ursu, Vasileios Stathias, Jianbin Duan, Nooshin Nabizadeh, Caty Chung, Christopher Mader, Ubbo Visser, Jeremy J Yang, Cristian G Bologa, Tudor I Oprea, Stephan C Schürer
BACKGROUND: One of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research and development resources. The Illuminating the Druggable Genome (IDG) project develops resources to catalyze the development of likely targetable, yet currently understudied prospective drug targets. A central component of the IDG program is a comprehensive knowledge resource of the druggable genome...
November 9, 2017: Journal of Biomedical Semantics
https://www.readbyqxmd.com/read/29118406/single-cell-co-expression-subnetwork-analysis
#7
Thomas E Bartlett, Sören Müller, Aaron Diaz
Single-cell transcriptomic data have rapidly become very popular in genomic science. Genomic science also has a long history of using network models to understand the way in which genes work together to carry out specific biological functions. However, working with single-cell data presents major challenges, such as zero inflation and technical noise. These challenges require methods to be specifically adapted to the context of single-cell data. Recently, much effort has been made to develop the theory behind statistical network models...
November 8, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29117534/building-predictive-models-of-genetic-circuits-using-the-principle-of-maximum-caliber
#8
Taylor Firman, Gábor Balázsi, Kingshuk Ghosh
Learning the underlying details of a gene network is a major challenge in cellular and synthetic biology. We address this challenge by building a chemical kinetic model that utilizes information encoded in the stochastic protein expression trajectories typically measured in experiments. The applicability of the proposed method is demonstrated in an auto-activating genetic circuit, a common motif in natural and synthetic gene networks. Our approach is based on the principle of maximum caliber (MaxCal)-a dynamical analog of the principle of maximum entropy-and builds a minimal model using only three constraints: 1) protein synthesis, 2) protein degradation, and 3) positive feedback...
November 7, 2017: Biophysical Journal
https://www.readbyqxmd.com/read/29113310/inference-of-time-delayed-gene-regulatory-networks-based-on-dynamic-bayesian-network-hybrid-learning-method
#9
Bin Yu, Jia-Meng Xu, Shan Li, Cheng Chen, Rui-Xin Chen, Lei Wang, Yan Zhang, Ming-Hui Wang
Gene regulatory networks (GRNs) research reveals complex life phenomena from the perspective of gene interaction, which is an important research field in systems biology. Traditional Bayesian networks have a high computational complexity, and the network structure scoring model has a single feature. Information-based approaches cannot identify the direction of regulation. In order to make up for the shortcomings of the above methods, this paper presents a novel hybrid learning method (DBNCS) based on dynamic Bayesian network (DBN) to construct the multiple time-delayed GRNs for the first time, combining the comprehensive score (CS) with the DBN model...
October 6, 2017: Oncotarget
https://www.readbyqxmd.com/read/29100075/comprehensive-and-integrated-genomic-characterization-of-adult-soft-tissue-sarcomas
#10
(no author information available yet)
Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (TP53, ATRX, RB1) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors...
November 2, 2017: Cell
https://www.readbyqxmd.com/read/29097749/a-novel-mirna-analysis-framework-to-analyze-differential-biological-networks
#11
Ankush Bansal, Tiratha Raj Singh, Rajinder Singh Chauhan
For understanding complex biological systems, a systems biology approach, involving both the top-down and bottom-up analyses, is often required. Numerous system components and their connections are best characterised as networks, which are primarily represented as graphs, with several nodes connected at multiple edges. Inefficient network visualisation is a common problem related to transcriptomic and genomic datasets. In this article, we demonstrate an miRNA analysis framework with the help of Jatropha curcas healthy and disease transcriptome datasets, functioning as a pipeline derived from the graph theory universe, and discuss how the network theory, along with gene ontology (GO) analysis, can be used to infer biological properties and other important features of a network...
November 6, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29082853/cancer-gene-profiling-in-non-small-cell-lung-cancers-reveals-activating-mutations-in-jak2-and-jak3-with-therapeutic-implications
#12
Shuyu D Li, Meng Ma, Hui Li, Aneta Waluszko, Tatyana Sidorenko, Eric E Schadt, David Y Zhang, Rong Chen, Fei Ye
BACKGROUND: Next-generation sequencing (NGS) of cancer gene panels are widely applied to enable personalized cancer therapy and to identify novel oncogenic mutations. METHODS: We performed targeted NGS on 932 clinical cases of non-small-cell lung cancers (NSCLCs) using the Ion AmpliSeq™ Cancer Hotspot panel v2 assay. RESULTS: Actionable mutations were identified in 65% of the cases with available targeted therapeutic options, including 26% of the patients with mutations in National Comprehensive Cancer Network (NCCN) guideline genes...
October 30, 2017: Genome Medicine
https://www.readbyqxmd.com/read/29082337/inference-of-cell-type-specific-regulatory-networks-on-mammalian-lineages
#13
Deborah Chasman, Sushmita Roy
Transcriptional regulatory networks are at the core of establishing cell type specific gene expression programs. In mammalian systems, such regulatory networks are determined by multiple levels of regulation, including by transcription factors, chromatin environment, and three-dimensional organization of the genome. Recent efforts to measure diverse regulatory genomic datasets across multiple cell types and tissues offer unprecedented opportunities to examine the context-specificity and dynamics of regulatory networks at a greater resolution and scale than before...
April 2017: Current opinion in systems biology
https://www.readbyqxmd.com/read/29081784/eqtls-regulating-transcript-variations-associated-with-rapid-internode-elongation-in-deepwater-rice
#14
Takeshi Kuroha, Keisuke Nagai, Yusuke Kurokawa, Yoshiaki Nagamura, Miyako Kusano, Hideshi Yasui, Motoyuki Ashikari, Atsushi Fukushima
To avoid low oxygen, oxygen deficiency or oxygen deprivation, deepwater rice cultivated in flood planes can develop elongated internodes in response to submergence. Knowledge of the gene regulatory networks underlying rapid internode elongation is important for an understanding of the evolution and adaptation of major crops in response to flooding. To elucidate the genetic and molecular basis controlling their deepwater response we used microarrays and performed expression quantitative trait loci (eQTL) and phenotypic QTL (phQTL) analyses of internode samples of 85 recombinant inbred line (RIL) populations of non-deepwater (Taichung 65)- and deepwater rice (Bhadua)...
2017: Frontiers in Plant Science
https://www.readbyqxmd.com/read/29080613/phylogeography-genetic-variability-and-structure-of-acanthamoeba-metapopulations-in-iran-inferred-by-18s-ribosomal-rna-sequences-a-systematic-review-and-meta-analysis
#15
REVIEW
Adel Spotin, Hamid Reza Moslemzadeh, Mahmoud Mahami-Oskouei, Ehsan Ahmadpour, Maryam Niyyati, Seyed Hossein Hejazi, Fatemeh Memari, Jafar Noori
OBJECTIVE: To verify phylogeography and genetic structure of Acanthamoeba populations among the Iranian clinical isolates and natural/artificial environments distributed in various regions of the country. METHODS: We searched electronic databases including Medline, PubMed, Science Direct, Scopus and Google Scholar from 2005 to 2016. To explore the genetic variability of Acanthamoeba sp, 205 sequences were retrieved from keratitis patients, immunosuppressed cases and environmental sources as of various geographies of Iran...
September 2017: Asian Pacific Journal of Tropical Medicine
https://www.readbyqxmd.com/read/29072883/highly-interwoven-communities-of-a-gene-regulatory-network-unveil-topologically-important-genes-for-maize-seed-development
#16
Wenwei Xiong, Chunlei Wang, Xiangbo Zhang, Qinghua Yang, Ruixin Shao, Jinsheng Lai, Chunguang Du
The complex interactions between transcription factors (TFs) and their target genes in a spatially and temporally specific manner are crucial to all cellular processes. Reconstruction of gene regulatory networks (GRNs) from gene expression profiles can help to decipher TF-gene regulations in a variety of contexts. However, the inevitable prediction errors of GRNs hinder optimal data mining of RNA-Seq transcriptome profiles. Here we perform an integrative study of maize seed development in order to identify key genes in a complex developmental process...
October 26, 2017: Plant Journal: for Cell and Molecular Biology
https://www.readbyqxmd.com/read/29067091/identifying-key-genes-in-glaucoma-based-on-a-benchmarked-dataset-and-the-gene-regulatory-network
#17
Xi Chen, Qiao-Ling Wang, Meng-Hui Zhang
The current study aimed to identify key genes in glaucoma based on a benchmarked dataset and gene regulatory network (GRN). Local and global noise was added to the gene expression dataset to produce a benchmarked dataset. Differentially-expressed genes (DEGs) between patients with glaucoma and normal controls were identified utilizing the Linear Models for Microarray Data (Limma) package based on benchmarked dataset. A total of 5 GRN inference methods, including Zscore, GeneNet, context likelihood of relatedness (CLR) algorithm, Partial Correlation coefficient with Information Theory (PCIT) and GEne Network Inference with Ensemble of Trees (Genie3) were evaluated using receiver operating characteristic (ROC) and precision and recall (PR) curves...
October 2017: Experimental and Therapeutic Medicine
https://www.readbyqxmd.com/read/29053381/adaptive-networkprofiler-for-identifying-cancer-characteristic-specific-gene-regulatory-networks
#18
Heewon Park, Teppei Shimamura, Seiya Imoto, Satoru Miyano
There is currently much discussion about sample (patient)-specific gene regulatory network identification, since the efficiently constructed sample-specific gene networks lead to effective personalized cancer therapy. Although statistical approaches have been proposed for inferring gene regulatory networks, the methods cannot reveal sample-specific characteristics because the existing methods, such as an L1-type regularization, provide averaged results for all samples. Thus, we cannot reveal sample-specific characteristics in transcriptional regulatory networks...
October 20, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/29051499/an-integrative-method-to-decode-regulatory-logics-in-gene-transcription
#19
Bin Yan, Daogang Guan, Chao Wang, Junwen Wang, Bing He, Jing Qin, Kenneth R Boheler, Aiping Lu, Ge Zhang, Hailong Zhu
Modeling of transcriptional regulatory networks (TRNs) has been increasingly used to dissect the nature of gene regulation. Inference of regulatory relationships among transcription factors (TFs) and genes, especially among multiple TFs, is still challenging. In this study, we introduced an integrative method, LogicTRN, to decode TF-TF interactions that form TF logics in regulating target genes. By combining cis-regulatory logics and transcriptional kinetics into one single model framework, LogicTRN can naturally integrate dynamic gene expression data and TF-DNA-binding signals in order to identify the TF logics and to reconstruct the underlying TRNs...
October 19, 2017: Nature Communications
https://www.readbyqxmd.com/read/29050346/identification-of-candidate-genes-related-to-pancreatic-cancer-based-on-analysis-of-gene-co-expression-and-protein-protein-interaction-network
#20
Tiejun Zhang, Xiaojuan Wang, Zhenyu Yue
Pancreatic cancer (PC) is one of the most common causes of cancer mortality worldwide. As the genetic mechanism of this complex disease is not uncovered clearly, identification of related genes of PC is of great significance that could provide new insights into gene function as well as potential therapy targets. In this study, we performed an integrated network method to discover PC candidate genes based on known PC related genes. Utilizing the subnetwork extraction algorithm with gene co-expression profiles and protein-protein interaction data, we obtained the integrated network comprising of the known PC related genes (denoted as seed genes) and the putative genes (denoted as linker genes)...
September 19, 2017: Oncotarget
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