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Developments in Algorithms for Sequence Alignment: A Review.

Jiannan Chao1, Furong Tang2,3, Lei Xu3

  • 1Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China.

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Summary
This summary is machine-generated.

Advancements in sequencing technology drive the need for faster, accurate sequence alignment software. This review summarizes prevailing algorithms and quality estimation methods for multiple sequence alignment tools.

Keywords:
alignment quality estimationalignment refinementalignment scoringheuristic alignment algorithmsmultiple sequence alignment

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High-throughput sequencing technologies generate vast amounts of biological data.
  • Efficient and accurate sequence alignment is crucial for biological data analysis.
  • Existing algorithms and tools address diverse biological research needs.

Purpose of the Study:

  • To review prevailing sequence alignment algorithms.
  • To summarize quality estimation methods for multiple sequence alignment tools.
  • To provide an overview of current trends in sequence alignment research.

Main Methods:

  • Literature review of sequence alignment algorithms.
  • Analysis of existing multiple sequence alignment tools.
  • Summary of quality assessment techniques.

Main Results:

  • Identification of key algorithms driving sequence alignment.
  • Overview of various software solutions for sequence alignment.
  • Discussion of methods for evaluating the quality of multiple sequence alignments.

Conclusions:

  • The field of sequence alignment is rapidly evolving due to technological advancements.
  • Accurate quality estimation is vital for reliable biological data interpretation.
  • Further development in alignment algorithms and quality metrics is needed.