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Gene network inference

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https://www.readbyqxmd.com/read/28528256/evaluation-of-artificial-time-series-microarray-data-for-dynamic-gene-regulatory-network-inference
#1
P Xenitidis, I Seimenis, S Kakolyris, A Adamopoulos
High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process...
May 17, 2017: Journal of Theoretical Biology
https://www.readbyqxmd.com/read/28526529/adding-biological-meaning-to-human-protein-protein-interactions-identified-by-yeast-two-hybrid-screenings-a-guide-through-bioinformatics-tools
#2
Juliana Felgueiras, Joana Vieira Silva, Margarida Fardilha
"A man is known by the company he keeps" is a popular expression that perfectly fits proteins. A common approach to characterize the function of a target protein is to identify its interacting partners and thus infer its roles based on the known functions of the interactors. Protein-protein interaction networks (PPINs) have been created for several organisms, including humans, primarily as results of high-throughput screenings, such as yeast two-hybrid (Y2H). Their unequivocal use to understand events underlying human pathophysiology is promising in identifying genes and proteins associated with diseases...
May 16, 2017: Journal of Proteomics
https://www.readbyqxmd.com/read/28520713/combining-inferred-regulatory-and-reconstructed-metabolic-networks-enhances-phenotype-prediction-in-yeast
#3
Zhuo Wang, Samuel A Danziger, Benjamin D Heavner, Shuyi Ma, Jennifer J Smith, Song Li, Thurston Herricks, Evangelos Simeonidis, Nitin S Baliga, John D Aitchison, Nathan D Price
Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models...
May 17, 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28515146/transcriptome-of-wheat-inflorescence-development-from-spikelet-initiation-to-floral-patterning
#4
Nan Feng, Gaoyuan Song, Jiantao Guan, Kai Chen, Meiling Jia, Dehua Huang, Jiajie Wu, Lichao Zhang, Xiuying Kong, Shuaifeng Geng, Jun Liu, Aili Li, Long Mao
Early reproductive development in cereals is crucial for final grain number per spike, and hence the yield potential of the crop. To date, however, no systematic analyses of gene expression profiles during this important process have been conducted for common wheat (Triticum aestivum). Here, we studied the transcriptome profiles at four stages of early wheat reproductive development, from spikelet initiation to floral organ differentiation. K-means clustering and stage-specific transcript identification detected dynamically expressed homoeologs of important transcription regulators in spikelet and floral meristems that may be involved in spikelet initiation, floret meristem specification, and floral organ patterning, as inferred from their homologs in model plants...
May 17, 2017: Plant Physiology
https://www.readbyqxmd.com/read/28510607/recent-evolutionary-history-of-chrysoperla-externa-hagen-1861-neuroptera-chrysopidae-in-brazil
#5
Adriana C Morales-Corrêa E Castro, Nara Cristina Chiarini Pena Barbosa
This work aimed to elucidate the distribution of Chrysoperla externa haplotypes and investigate whether it exhibits structure based on genetic composition as opposed to geographic location. The genetic diversity of C. externa, analyzed by AMOVA using the COI and 16S rRNA genes as mitochondrial markers, showed significant haplotype structure arising from genetic differences that was not associated with sampling location. This was reflected in the network grouping. Bayesian inference showed that haplotype distribution may have its origins in C...
2017: PloS One
https://www.readbyqxmd.com/read/28505768/community-detection-link-prediction-and-layer-interdependence-in-multilayer-networks
#6
Caterina De Bacco, Eleanor A Power, Daniel B Larremore, Cristopher Moore
Complex systems are often characterized by distinct types of interactions between the same entities. These can be described as a multilayer network where each layer represents one type of interaction. These layers may be interdependent in complicated ways, revealing different kinds of structure in the network. In this work we present a generative model, and an efficient expectation-maximization algorithm, which allows us to perform inference tasks such as community detection and link prediction in this setting...
April 2017: Physical Review. E
https://www.readbyqxmd.com/read/28505156/an-independent-component-analysis-confounding-factor-correction-framework-for-identifying-broad-impact-expression-quantitative-trait-loci
#7
Jin Hyun Ju, Sushila A Shenoy, Ronald G Crystal, Jason G Mezey
Genome-wide expression Quantitative Trait Loci (eQTL) studies in humans have provided numerous insights into the genetics of both gene expression and complex diseases. While the majority of eQTL identified in genome-wide analyses impact a single gene, eQTL that impact many genes are particularly valuable for network modeling and disease analysis. To enable the identification of such broad impact eQTL, we introduce CONFETI: Confounding Factor Estimation Through Independent component analysis. CONFETI is designed to address two conflicting issues when searching for broad impact eQTL: the need to account for non-genetic confounding factors that can lower the power of the analysis or produce broad impact eQTL false positives, and the tendency of methods that account for confounding factors to model broad impact eQTL as non-genetic variation...
May 15, 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28500050/a-systemic-analysis-of-transcriptomic-and-epigenomic-data-to-reveal-regulation-patterns-for-complex-disease
#8
Chao Xu, Ji-Gang Zhang, Dongdong Lin, Lan Zhang, Hui Shen, Hong-Wen Deng
Integrating diverse genomics data can provide a global view of the complex biological processes related to the human complex diseases. Although substantial efforts have been made to integrate different omics data, there are at least three challenges for multi-omics integration methods: (i) How to simultaneously consider the effects of various genomic factors, since these factors jointly influence the phenotypes; (ii) How to effectively incorporate the information from publicly accessible databases and omics datasets to fully capture the interactions among (epi-)genomic factors from diverse omics data; and (iii) Until present, the combination of >2 omics datasets has been poorly explored...
May 12, 2017: G3: Genes—Genomes—Genetics
https://www.readbyqxmd.com/read/28498958/complexview-a-server-for-the-interpretation-of-protein-abundance-and-connectivity-information-to-identify-protein-complexes
#9
Victor Solis-Mezarino, Franz Herzog
The molecular understanding of cellular processes requires the identification and characterization of the involved protein complexes. Affinity-purification and mass spectrometric analysis (AP-MS) are performed on a routine basis to detect proteins assembled in complexes. In particular, protein abundances obtained by quantitative mass spectrometry and direct protein contacts detected by crosslinking and mass spectrometry (XL-MS) provide complementary datasets for revealing the composition, topology and interactions of modules in a protein network...
May 12, 2017: Nucleic Acids Research
https://www.readbyqxmd.com/read/28489411/gcoda-conditional-dependence-network-inference-for-compositional-data
#10
Huaying Fang, Chengcheng Huang, Hongyu Zhao, Minghua Deng
The increasing quality and the reducing cost of high-throughput sequencing technologies for 16S rRNA gene profiling enable researchers to directly analyze microbe communities in natural environments. The direct interactions among microbial species of a given ecological system can help us understand the principles of community assembly and maintenance under various conditions. Compositionality and dimensionality of microbiome data are two main challenges for inferring the direct interaction network of microbes...
May 10, 2017: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://www.readbyqxmd.com/read/28485748/genespider-gene-regulatory-network-inference-benchmarking-with-controlled-network-and-data-properties
#11
Andreas Tjärnberg, Daniel C Morgan, Matthew Studham, Torbjörn E M Nordling, Erik L L Sonnhammer
A key question in network inference, that has not been properly answered, is what accuracy can be expected for a given biological dataset and inference method. We present GeneSPIDER - a Matlab package for tuning, running, and evaluating inference algorithms that allows independent control of network and data properties to enable data-driven benchmarking. GeneSPIDER is uniquely suited to address this question by first extracting salient properties from the experimental data and then generating simulated networks and data that closely match these properties...
May 9, 2017: Molecular BioSystems
https://www.readbyqxmd.com/read/28484519/study-of-meta-analysis-strategies-for-network-inference-using-information-theoretic-approaches
#12
Ngoc C Pham, Benjamin Haibe-Kains, Pau Bellot, Gianluca Bontempi, Patrick E Meyer
BACKGROUND: Reverse engineering of gene regulatory networks (GRNs) from gene expression data is a classical challenge in systems biology. Thanks to high-throughput technologies, a massive amount of gene-expression data has been accumulated in the public repositories. Modelling GRNs from multiple experiments (also called integrative analysis) has; therefore, naturally become a standard procedure in modern computational biology. Indeed, such analysis is usually more robust than the traditional approaches, which suffer from experimental biases and the low number of samples by analysing individual datasets...
2017: BioData Mining
https://www.readbyqxmd.com/read/28482794/inferring-mirna-sponge-co-regulation-of-protein-protein-interactions-in-human-breast-cancer
#13
Junpeng Zhang, Thuc Duy Le, Lin Liu, Jiuyong Li
BACKGROUND: Recent studies have shown that the crosstalk between microRNA (miRNA) sponges plays an important role in human cancers. However, the co-regulation roles of miRNA sponges in protein-protein interactions (PPIs) are still unknown. RESULTS: In this study, we propose a multi-step method called miRSCoPPI to infer miRNA sponge co-regulation of PPIs. We focus on investigating breast cancer (BRCA) related miRNA sponge co-regulation, by integrating heterogeneous data, including miRNA, long non-coding RNA (lncRNA) and messenger RNA (mRNA) expression data, experimentally validated miRNA-target interactions, PPIs and lncRNA-target interactions, and the list of breast cancer genes...
May 8, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28479871/constructing-networks-of-organelle-functional-modules-in-arabidopsis
#14
Jiajie Penga, Tao Wang, Jianping Huc, Yadong Wang, Jin Chen
With the rapid accumulation of gene expression data, gene functional module identification has become a widely used approach in functional analysis. However, tools to identify organelle functional modules and analyze their relationships are still missing. We present a soft thresholding approach to construct networks of functional modules using gene expression datasets, in which nodes are strongly co-expressed genes that encode proteins residing in the same subcellular localization, and links represent strong inter-module connections...
October 2016: Current Genomics
https://www.readbyqxmd.com/read/28479747/elucidation-of-the-sequential-transcriptional-activity-in-escherichia-coli-using-time-series-rna-seq-data
#15
Pui Shan Wong, Kosuke Tashiro, Satoru Kuhara, Sachiyo Aburatani
Functional genomics and gene regulation inference has readily expanded our knowledge and understanding of gene interactions with regards to expression regulation. With the advancement of transcriptome sequencing in time-series comes the ability to study the sequential changes of the transcriptome. Here, we present a new method to augment regulation networks accumulated in literature with transcriptome data gathered from time-series experiments to construct a sequential representation of transcription factor activity...
2017: Bioinformation
https://www.readbyqxmd.com/read/28473844/functional-characterization-of-a-putative-glycine-max-elf4-in-transgenic-arabidopsis-and-its-role-during-flowering-control
#16
Juliana Marcolino-Gomes, Thiago J Nakayama, Hugo B C Molinari, Marcos F Basso, Liliane M M Henning, Renata Fuganti-Pagliarini, Frank G Harmon, Alexandre L Nepomuceno
Flowering is an important trait in major crops like soybean due to its direct relation to grain production. The circadian clock mediates the perception of seasonal changes in day length and temperature to modulate flowering time. The circadian clock gene EARLY FLOWERING 4 (ELF4) was identified in Arabidopsis thaliana and is believed to play a key role in the integration of photoperiod, circadian regulation, and flowering. The molecular circuitry that comprises the circadian clock and flowering control in soybeans is just beginning to be understood...
2017: Frontiers in Plant Science
https://www.readbyqxmd.com/read/28472402/cofactor-improved-protein-function-prediction-by-combining-structure-sequence-and-protein-protein-interaction-information
#17
Chengxin Zhang, Peter L Freddolino, Yang Zhang
The COFACTOR web server is a unified platform for structure-based multiple-level protein function predictions. By structurally threading low-resolution structural models through the BioLiP library, the COFACTOR server infers three categories of protein functions including gene ontology, enzyme commission and ligand-binding sites from various analogous and homologous function templates. Here, we report recent improvements of the COFACTOR server in the development of new pipelines to infer functional insights from sequence profile alignments and protein-protein interaction networks...
May 2, 2017: Nucleic Acids Research
https://www.readbyqxmd.com/read/28472169/identifying-novel-fruit-related-genes-in-arabidopsis-thaliana-based-on-the-random-walk-with-restart-algorithm
#18
Yunhua Zhang, Li Dai, Ying Liu, YuHang Zhang, ShaoPeng Wang
Fruit is essential for plant reproduction and is responsible for protection and dispersal of seeds. The development and maturation of fruit is tightly regulated by numerous genetic factors that respond to environmental and internal stimulation. In this study, we attempted to identify novel fruit-related genes in a model organism, Arabidopsis thaliana, using a computational method. Based on validated fruit-related genes, the random walk with restart (RWR) algorithm was applied on a protein-protein interaction (PPI) network using these genes as seeds...
2017: PloS One
https://www.readbyqxmd.com/read/28469803/construction-and-analysis-of-the-transcription-factor-microrna-co-regulatory-network-response-to-mycobacterium-tuberculosis-a-view-from-the-blood
#19
Yan Lin, Zipeng Duan, Feng Xu, Jiayuan Zhang, Marina V Shulgina, Fan Li
Mycobacterium tuberculosis (Mtb) infection has been regional outbreak, recently. The traditional focus on the patterns of "reductionism" which was associated with single molecular changes has been unable to meet the demand of early diagnosis and clinical application when current tuberculosis infection happened. In this study, we employed a systems biology approach to collect large microarray data sets including mRNAs and microRNAs (miRNAs) to identify the differentially expressed mRNAs and miRNAs in the whole blood of TB patients...
2017: American Journal of Translational Research
https://www.readbyqxmd.com/read/28469387/integrative-analysis-of-gene-networks-and-their-application-to-lung-adenocarcinoma-studies
#20
Sangin Lee, Faming Liang, Ling Cai, Guanghua Xiao
The construction of gene regulatory networks (GRNs) is an essential component of biomedical research to determine disease mechanisms and identify treatment targets. Gaussian graphical models (GGMs) have been widely used for constructing GRNs by inferring conditional dependence among a set of gene expressions. In practice, GRNs obtained by the analysis of a single data set may not be reliable due to sample limitations. Therefore, it is important to integrate multiple data sets from comparable studies to improve the construction of a GRN...
2017: Cancer Informatics
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