Evidence map›Paper›PMID 34573438›Full record

ArticleGenes2021

Improved Large-Scale Homology Search by Two-Step Seed Search Using Multiple Reduced Amino Acid Alphabets.

Kazuki Takabatake, Kazuki Izawa, Motohiro Akikawa, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama

Abstract read
In one paragraph

Article in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Kazuki TakabatakeDepartment of Computer Science, School of Computing, Tokyo Institute of Technology, Tokyo 152-8550, Japan.ORCID 0000-0002-1138-2599
Kazuki IzawaDepartment of Computer Science, School of Computing, Tokyo Institute of Technology, Tokyo 152-8550, Japan.ORCID 0000-0003-2509-5563
Motohiro AkikawaDepartment of Computer Science, School of Computing, Tokyo Institute of Technology, Tokyo 152-8550, Japan.ORCID 0000-0002-3428-0640
Keisuke YanagisawaDepartment of Computer Science, School of Computing, Tokyo Institute of Technology, Tokyo 152-8550, Japan.ORCID 0000-0003-0224-0035
Masahito OhueDepartment of Computer Science, School of Computing, Tokyo Institute of Technology, Tokyo 152-8550, Japan.ORCID 0000-0002-0120-1643
Yutaka AkiyamaDepartment of Computer Science, School of Computing, Tokyo Institute of Technology, Tokyo 152-8550, Japan.ORCID 0000-0003-2863-8703

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metagenomic analysis, a technique used to comprehensively analyze microorganisms present in the environment, requires performing high-precision homology searches on large amounts of sequencing data, the size of which has increased dramatically with the development of next-generation sequencing. NCBI BLAST is the most widely used software for performing homology searches, but its speed is insufficient for the throughput of current DNA sequencers. In this paper, we propose a new, high-performance homology search algorithm that employs a two-step seed search strategy using multiple reduced amino acid alphabets to identify highly similar subsequences. Additionally, we evaluated the validity of the proposed method against several existing tools. Our method was faster than any other existing program for ≤120,000 queries, while DIAMOND, an existing tool, was the fastest method for >120,000 queries.

Indexed as

Sequence Homology, Amino AcidAlgorithmsComputational BiologyInternetMetagenomicsgenome sequencehomology searchmetagenomic analysisreduced amino acid

Identifiers

PMID34573438
PMCPMC8469100

What OpenQuestion holds

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Registered trials

None linked

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.