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Analysis and modelling of septic shock microarray data using Singular Value Decomposition
Published in Academic Press Inc.
2017
PMID: 28499953
Volume: 70
   
Pages: 77 - 84
Abstract
Being a high throughput technique, enormous amounts of microarray data has been generated and there arises a need for more efficient techniques of analysis, in terms of speed and accuracy. Finding the differentially expressed genes based on just fold change and p-value might not extract all the vital biological signals that occur at a lower gene expression level. Besides this, numerous mathematical models have been generated to predict the clinical outcome from microarray data, while very few, if not none, aim at predicting the vital genes that are important in a disease progression. Such models help a basic researcher narrow down and concentrate on a promising set of genes which leads to the discovery of gene-based therapies. In this article, as a first objective, we have used the lesser known and used Singular Value Decomposition (SVD) technique to build a microarray data analysis tool that works with gene expression patterns and intrinsic structure of the data in an unsupervised manner. We have re-analysed a microarray data over the clinical course of Septic shock from Cazalis et al. (2014) and have shown that our proposed analysis provides additional information compared to the conventional method. As a second objective, we developed a novel mathematical model that predicts a set of vital genes in the disease progression that works by generating samples in the continuum between health and disease, using a simple normal-distribution-based random number generator. We also verify that most of the predicted genes are indeed related to septic shock. © 2017 Elsevier Inc.
About the journal
JournalJournal of Biomedical Informatics
PublisherAcademic Press Inc.
ISSN15320464
Open AccessYes
Concepts (60)
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    Gene expression
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    Gene therapy
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    Genes
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    Microarrays
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    Normal distribution
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    Number theory
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    Random number generation
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    DIFFERENTIALLY EXPRESSED GENE
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    GENE EXPRESSION LEVELS
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    GENE EXPRESSION PATTERNS
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    HIGH-THROUGHPUT TECHNIQUE
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    Microarray data analysis
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    PREDICTIVE MODELLING
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    Random number generators
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    SEPTIC SHOCKS
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    Singular value decomposition
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    Article
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    ASPH GENE
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    CD24 GENE
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    CEACAM1 GENE
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    CLINICAL ASSESSMENT TOOL
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    Comparative study
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    Disease course
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    Down regulation
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    GBP1 GENE
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    Gene
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    Gene control
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    GYPA GENE
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    GYPB GENE
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    HGF GENE
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    HPGD GENE
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    Human
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    IGK GENE
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    IGL GENE
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    ITGB3 GENE
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    MALAT1 GENE
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    Mathematical model
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    Microarray analysis
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    OCLN GENE
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    Priority journal
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    RORA GENE
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    SEPTIC SHOCK
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    SMCHD1 GENE
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    SNCA GENE
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    STAT1 GENE
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    TNS1 GENE
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    Upregulation
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    XIST GENE
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    Algorithm
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    Biology
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    Dna microarray
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    Gene expression profiling
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    SEPTIC SHOCK
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    Theoretical model
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    Algorithms
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    Computational biology
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    Humans
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    Models, theoretical
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    Oligonucleotide array sequence analysis
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    SHOCK, SEPTIC