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[Software development in data analysis and mining for cDNA microarray].

Bin Wu1, Jianguo Wang, Miqu Wang

  • 1Institute of Integrative Chinese and Western Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China.

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi = Journal of Biomedical Engineering = Shengwu Yixue Gongchengxue Zazhi
|February 1, 2008
PubMed
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This paper reviews software for cDNA microarray data analysis. It covers data acquisition, statistical analysis, and gene network data mining for improved insights.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Context:

  • Microarray technology generates large datasets requiring sophisticated analysis.
  • Software development is crucial for effective microarray data interpretation.
  • Advancements in computational tools drive progress in molecular biology research.

Purpose:

  • To provide a comprehensive overview of current software developments for cDNA microarray data analysis.
  • To categorize and discuss software tools across key stages of data processing.
  • To highlight the evolution of techniques in microarray data mining.

Summary:

  • The paper details software for cDNA microarray data analysis, covering three main stages.
  • It discusses data acquisition from experiments, statistical methods for data treatment, and data mining approaches for gene networks.

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  • Emphasis is placed on the state-of-the-art software solutions available.

    • Impact:

    • Facilitates researchers in selecting appropriate software for their cDNA microarray studies.
    • Aids in understanding the landscape of bioinformatics tools for gene expression analysis.
    • Contributes to the advancement of data mining techniques in genomics and systems biology.