Evidence map›Paper›PMID 31665271›Full record

ArticleBioinformatics (Oxford, England)2019

Kalign 3: multiple sequence alignment of large data sets.

Timo Lassmann

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers.

0numbers the graph read from it
0cells of the map it votes in
89citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

89 citing papers in PubMed.

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  15. Spatiotemporal dynamics of benthicFrontiers in microbiology · 2026
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29 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Timo LassmannTelethon Kids Institute, University of Western Australia, Nedlands, WA, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationKalign is an efficient multiple sequence alignment (MSA) program capable of aligning thousands of protein or nucleotide sequences. However, current alignment problems involving large numbers of sequences are exceeding Kalign's original design specifications. Here we present a completely re-written and updated version to meet current and future alignment challenges.

resultsKalign now uses a SIMD accelerated version of the bit-parallel Gene Myers algorithm to estimate pariwise distances, adopts a sequence embedding strategy and the bi-secting K-means algorithm to rapidly construct guide trees for thousands of sequences. The new version maintains high alignment accuracy on both protein and nucleotide alignments and scales better than other MSA tools. AVAILABILITY: The source code of Kalign and code to reproduce the results are found here: https://github.com/timolassmann/kalign.

Identifiers

PMID31665271
PMCPMC7703769

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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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.