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Using spreadsheet languages to understand sequence analysis algorithms.

M Bernstein1

  • 1Central Research and Development Department, E.I. du Pont de Nemours & Co., Inc., Wilmington, DE 19898.

Computer Applications in the Biosciences : CABIOS
|September 1, 1987
PubMed
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Spreadsheet programming offers powerful non-numerical applications beyond basic calculations. Implementing sequence analysis tools in spreadsheets clarifies algorithms and reveals parallel processing opportunities.

Area of Science:

  • Computational biology
  • Bioinformatics
  • Computer science

Background:

  • Spreadsheet software is widely used for numerical tasks.
  • The potential of spreadsheets for non-numerical applications, such as sequence analysis, is underexplored.

Purpose of the Study:

  • To demonstrate the utility of spreadsheet implementations for sequence analysis tools.
  • To highlight how spreadsheet notation can enhance algorithm understanding and experimentation.
  • To explore the potential of spreadsheets for parallel computing in bioinformatics.

Main Methods:

  • Implementation of established sequence analysis algorithms using spreadsheet formulas and functions.
  • Comparative analysis of spreadsheet-based algorithms versus traditional implementations.

Related Experiment Videos

  • Identification of inherent parallelism within spreadsheet structures for computational tasks.

    • Main Results:

    • Spreadsheet implementations effectively perform sequence analysis tasks.
    • The visual nature of spreadsheets simplifies algorithm comprehension and encourages user interaction.
    • Visible parallelism in spreadsheets suggests avenues for accelerating computationally intensive analyses.

    Conclusions:

    • Spreadsheets provide an accessible and intuitive platform for sequence analysis.
    • Spreadsheet-based approaches can demystify complex algorithms and foster innovation.
    • The parallel processing capabilities inherent in spreadsheets offer a promising direction for future research in computational biology.