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Exe-Muscle: An Exercised Human Skeletal Muscle Gene Expression Database

Author

Listed:
  • Kaiyuan Huang

    (School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, China
    These authors contributed equally to this work.)

  • Jingwen Song

    (School of Life Sciences, Zhengzhou University, Zhengzhou 450001, China
    These authors contributed equally to this work.)

  • Weishuai Kong

    (School of Life Sciences, Zhengzhou University, Zhengzhou 450001, China)

  • Zhongyuan Deng

    (School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, China
    School of Life Sciences, Zhengzhou University, Zhengzhou 450001, China)

Abstract

Human muscle tissue undergoes dynamic changes in gene expression during exercise, and the dynamics of these genes are correlated with muscle adaptation to exercise. A database of gene expression changes in human muscle before and after exercise was established for data mining. A web-based searchable database, Exe-muscle, was developed using microarray sequencing data, which can help users to retrieve gene expression at different times. Search results provide a complete description of target genes or genes with specific expression patterns. We can explore the molecular mechanisms behind exercise science by studying the changes in muscle gene expression over time before and after exercise. Based on the high-throughput microarray data before and after human exercise, a human pre- and post-exercise database was created using web-based database technology, which researchers can use or share their gene expression data. The Exe-muscle database is accessible online.

Suggested Citation

  • Kaiyuan Huang & Jingwen Song & Weishuai Kong & Zhongyuan Deng, 2022. "Exe-Muscle: An Exercised Human Skeletal Muscle Gene Expression Database," IJERPH, MDPI, vol. 19(14), pages 1-12, July.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:14:p:8806-:d:867056
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    References listed on IDEAS

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    1. Henry C Chung & Don R Keiller & Justin D Roberts & Dan A Gordon, 2021. "Do exercise-associated genes explain phenotypic variance in the three components of fitness? a systematic review & meta-analysis," PLOS ONE, Public Library of Science, vol. 16(10), pages 1-18, October.
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