ArticleNAR genomics and bioinformatics2024
ReAlign-N: an integrated realignment approach for multiple nucleic acid sequence alignment, combining global and local realignments.
Article in NAR genomics and bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- deMEM: a novel divide-and-conquer framework based on de Bruijn graph for scalable multiple sequence alignment.GigaScience · 2026Article
- ReAlign-P: a vertical iterative realignment method for protein multiple sequence alignment.Bioinformatics (Oxford, England) · 2025Article
- Advances in post-processing methods for multiple sequence alignment.Frontiers in genetics · 2025Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ensuring accurate multiple sequence alignment (MSA) is essential for comprehensive biological sequence analysis. However, the complexity of evolutionary relationships often results in variations that generic alignment tools may not adequately address. Realignment is crucial to remedy this issue. Currently, there is a lack of realignment methods tailored for nucleic acid sequences, particularly for lengthy sequences. Thus, there's an urgent need for the development of realignment methods better suited to address these challenges. This study presents ReAlign-N, a realignment method explicitly designed for multiple nucleic acid sequence alignment. ReAlign-N integrates both global and local realignment strategies for improved accuracy. In the global realignment phase, ReAlign-N incorporates K-Band and innovative memory-saving technology into the dynamic programming approach, ensuring high efficiency and minimal memory requirements for large-scale realignment tasks. The local realignment stage employs full matching and entropy scoring methods to identify low-quality regions and conducts realignment through MAFFT. Experimental results demonstrate that ReAlign-N consistently outperforms initial alignments on simulated and real datasets. Furthermore, compared to ReformAlign, the only existing multiple nucleic acid sequence realignment tool, ReAlign-N, exhibits shorter running times and occupies less memory space. The source code and test data for ReAlign-N are available on GitHub (https://github.com/malabz/ReAlign-N).
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.