Evidence map›Paper›PMID 30535314›Full record

ArticleGigaScience2019

Prot-SpaM: fast alignment-free phylogeny reconstruction based on whole-proteome sequences.

Chris-Andre Leimeister, Jendrik Schellhorn, Svenja Dörrer, Michael Gerth, Christoph Bleidorn, Burkhard Morgenstern

Abstract read
In one paragraph

Article in GigaScience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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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.

Chris-Andre LeimeisterUniversity of Göttingen, Department of Bioinformatics, Goldschmidtstr. 1, 37077 Göttingen, Germany.
Jendrik SchellhornUniversity of Göttingen, Department of Bioinformatics, Goldschmidtstr. 1, 37077 Göttingen, Germany.
Svenja DörrerUniversity of Göttingen, Department of Bioinformatics, Goldschmidtstr. 1, 37077 Göttingen, Germany.
Michael GerthInstitute for Integrative Biology, University of Liverpool, Biosciences Building, Crown Street, L69 7ZB Liverpool, UK.
Christoph BleidornUniversity of Göttingen, Department of Animal Evolution and Biodiversity, Untere Karspüle 2, 37073 Göttingen, Germany.
Burkhard MorgensternUniversity of Göttingen, Department of Bioinformatics, Goldschmidtstr. 1, 37077 Göttingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Word-based or 'alignment-free' sequence comparison has become an active research area in bioinformatics. While previous word-frequency approaches calculated rough measures of sequence similarity or dissimilarity, some new alignment-free methods are able to accurately estimate phylogenetic distances between genomic sequences. One of these approaches is Filtered Spaced Word Matches. Here, we extend this approach to estimate evolutionary distances between complete or incomplete proteomes; our implementation of this approach is called Prot-SpaM. We compare the performance of Prot-SpaM to other alignment-free methods on simulated sequences and on various groups of eukaryotic and prokaryotic taxa. Prot-SpaM can be used to calculate high-quality phylogenetic trees for dozens of whole-proteome sequences in a matter of seconds or minutes and often outperforms other alignment-free approaches. The source code of our software is available through Github: https://github.com/jschellh/ProtSpaM.

Indexed as

PhylogenySoftwareAmino Acid SequenceAnimalsBacteriaDatabases, ProteinPlantsProteomeSequence AlignmentProteomealignment-freeamino-acid substitutionsdistance methodKimuramicro-alignmentphylogenyprotein comparisonproteomespaced wordsWolbachia

Identifiers

PMID30535314
PMCPMC6436989

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.