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Bioinformatics software development: Principles and future directions

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    1. The growing volume of biomedical big data is driving a tremendous demand for advanced bioinformatics software.

      Artificial intelligence (AI) is expected to accelerate and enhance the development process of bioinformatics software.

      AI-augmented cloud computing is paving the way for the future of autonomous research.

  • The bioinformatics software for analyzing biomedical data is essential for converting raw data into meaningful biological insights. In this review, we outline the key stages and considerations in the development of bioinformatics software, using clusterProfiler and CIRCexplorer2 as illustrative examples. Furthermore, we examine some established large-scale life sciences platforms and summarize the design principles in the era of big data and Artificial Intelligence (AI) for open science. Future large-scale platforms are expected to offer graphical programming languages and transition from the sharing of data and codes to that of physical resources. The AI revolution will alter the landscape of bioinformatics software development and redefine the research paradigm of life sciences.
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  • Cite this article:

    Ma X.-K., Yu Y., Huang T., et al., (2024). Bioinformatics software development: Principles and future directions. The Innovation Life 2(3): 100083. https://doi.org/10.59717/j.xinn-life.2024.100083
    Ma X.-K., Yu Y., Huang T., et al., (2024). Bioinformatics software development: Principles and future directions. The Innovation Life 2(3): 100083. https://doi.org/10.59717/j.xinn-life.2024.100083

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