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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.
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.
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.
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