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Related Experiment Videos

Computational complexity of algorithms for sequence comparison, short-read assembly and genome alignment.

Shakuntala Baichoo1, Christos A Ouzounis2

  • 1Department of Computer Science & Engineering, University of Mauritius, Réduit 80837, Mauritius.

Bio Systems
|April 11, 2017
PubMed
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This review systematically examines the computational complexity of sequence analysis algorithms, crucial for handling growing genomic data. Understanding algorithm efficiency is key for future advancements in comparative genomics and biological simulations.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genomics

Background:

  • Numerous algorithms exist for sequence comparison, short-read assembly, and whole-genome alignment.
  • These algorithms support high-throughput sequencing, genome biology applications, and comparative genomics research.
  • The computational complexity of these algorithms is often reported but not systematically reviewed for a broad audience.

Purpose of the Study:

  • To systematically review the space and time complexity of key sequence analysis algorithms.
  • To highlight the properties of these algorithms comprehensively.
  • To identify opportunities for optimizing algorithms and data structures.

Main Methods:

  • Systematic literature review of computational complexity in sequence analysis algorithms.
Keywords:
Bioinformatics algorithmsComputational complexityGenome alignmentSequence comparisonShort-read assembly

Related Experiment Videos

  • Analysis and synthesis of reported space and time complexity data.
  • Identification of trends and potential areas for algorithmic improvement.

    • Main Results:

    • A comprehensive overview of the computational complexity of essential sequence analysis algorithms.
    • Highlighting the significance of complexity for current and future genomic data challenges.
    • Identification of specific algorithms and their complexity characteristics.

    Conclusions:

    • Computational complexity is a critical, yet often overlooked, factor in sequence analysis.
    • Systematic review provides a foundation for future research in algorithm and data structure optimization.
    • Addressing complexity is vital for managing unprecedented genomic data scales and enabling advanced biological simulations.