caBIG™ VISDA: Modeling, visualization, and discovery for cluster analysis of genomic data

Zhu, Yangyong; Li, Huai; Miller, David J.; Wang, Zuyi; Xuan, Jianhua; Clarke, Robert; Hoffman, Eric P.; Wang, Yue Joseph

doi:10.1186/1471-2105-9-383

Cited by 13 publications

(6 citation statements)

References 64 publications

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“…Numerous computational algorithms have been developed to partition such coexpression clusters [91] , [98] . These approaches utilize differing theoretical frameworks for data partitioning, including clustering algorithms (e.g., hierarchical or partitional clustering), probabilistic graphical models [99] , [100] , matrix decomposition approaches [101] – [105] , and algorithms that incorporate multiple lines of experimental evidence [106] , [107] . The specific usefulness of such algorithms depends upon the intended use, as well as the benefits and limitations of these methods are reviewed elsewhere [90] , [93] , [98] .…”

Section: Discussionmentioning

confidence: 99%

Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

Ackerman

Summerfield

et al. 2011

PLoS ONE

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A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals.

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Section: Discussionmentioning

confidence: 99%

Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

Ackerman

Summerfield

et al. 2011

PLoS ONE

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“…To the best of our knowledge, the wording Human-Data Interaction was used for the first time in data visualization by Zhu et al in 2008 to refer to the analysis of multi-variate data [60]. HDI has also been used by Mortier et al [41] to investigate how personal data are collected and shared, the ethical implications surrounding the collection and use of data, and issues related with privacy and consent.…”

Section: Human-data Interaction (Hdi)mentioning

confidence: 99%

Move Your Body: Engaging Museum Visitors with Human-Data Interaction

Trajkova

Alhakamy

Cafaro

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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“…DT is an approach that can be used to establish tree-like models to for classification or prediction. Since clustering analysis of MD microarray data [14] has already revealed the hierarchical structure among different MD sub-types, we want to further investigate if tree based models can also facilitate classification of MD sub-types. We also use SVM classifier for this study since it is less prone to the curse-of-dimensionality problem intrinsic to the high dimensional microarray data [3].…”

Section: Methodsmentioning

confidence: 99%

Computational analysis of muscular dystrophy sub-types using a novel integrative scheme

Wang

Xuan

et al. 2012

Neurocomputing

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To construct biologically interpretable gene sets for muscular dystrophy (MD) sub-type classification, we propose a novel computational scheme to integrate protein-protein interaction (PPI) network, functional gene set information, and mRNA profiling data. The workflow of the proposed scheme includes the following three major steps: firstly, we apply an affinity propagation clustering (APC) approach to identify gene sub-networks associated with each MD sub-type, in which a new distance metric is proposed for APC to combine PPI network information and gene-gene co-expression relationship; secondly, we further incorporate functional gene set knowledge, which complements the physical PPI information, into our scheme for biomarker identification; finally, based on the constructed sub-networks and gene set features, we apply multi-class support vector machines (MSVMs) for MD sub-type classification, with which to highlight the biomarkers contributing to sub-type prediction. The experimental results show that our scheme can help identify sub-networks and gene sets that are more relevant to MD than those constructed by other conventional approaches. Moreover, our integrative strategy improves the prediction accuracy substantially, especially for those ’hard-to-classify’ sub-types.

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caBIG™ VISDA: Modeling, visualization, and discovery for cluster analysis of genomic data

Cited by 13 publications

References 64 publications

Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

Move Your Body: Engaging Museum Visitors with Human-Data Interaction

Computational analysis of muscular dystrophy sub-types using a novel integrative scheme

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