GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature.

The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly d...

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Published in:BioMed Research International Vol. 2015; pp. 1 - 9
Main Authors: Ye, Ning, Yin, Hengfu, Liu, Jingjing, Dai, Xiaogang, Yin, Tongming
Format: equations & formulas pictorial research tables/charts Journal Article
Published: Wiley-Blackwell 6/25/2015
Online Access:View this record in EBSCOhost
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      dt: 6/25/2015
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2015/853734
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        atl: GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature.
      aug:
        au:
          Ye, Ning
          Yin, Hengfu
          Liu, Jingjing
          Dai, Xiaogang
          Yin, Tongming
        affil: The Southern Modern Forestry Collaborative Innovation Center, Nanjing Forestry University, Nanjing 210037, China
      sug:
        subj:
          Gene Expression Evaluation
          Microarray Analysis
          Sequence Analysis
          Software Utilization
          Human
          Funding Source
          Genes
          Algorithms
          User-Computer Interface
          Data Analysis Software
          Regression
          P-Value
          Cell Physiology
          China
      ab: The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI) toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
        research
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        Journal Article
      ougenre: Article
    language: English
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