Evidence map›Paper›PMID 27703668›Full record

ArticleF1000Research2016

Protein domain architectures provide a fast, efficient and scalable alternative to sequence-based methods for comparative functional genomics.

Jasper J Koehorst, Edoardo Saccenti, Peter J Schaap, Vitor A P Martins Dos Santos, Maria Suarez-Diez

Abstract read
In one paragraph

Article in F1000Research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  10. Complete Genome Sequence ofGenome announcements · 2017
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  12. Draft Genome Sequence ofGenome announcements · 2017
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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

5 authors.

Jasper J KoehorstLaboratory of Systems and Synthetic Biology, Wageningen University and Research, Wageningen, Netherlands.ORCID 0000-0001-8172-8981
Edoardo SaccentiLaboratory of Systems and Synthetic Biology, Wageningen University and Research, Wageningen, Netherlands.
Peter J SchaapLaboratory of Systems and Synthetic Biology, Wageningen University and Research, Wageningen, Netherlands.
Vitor A P Martins Dos SantosLaboratory of Systems and Synthetic Biology, Wageningen University and Research, Wageningen, Netherlands.
Maria Suarez-DiezLaboratory of Systems and Synthetic Biology, Wageningen University and Research, Wageningen, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A functional comparative genome analysis is essential to understand the mechanisms underlying bacterial evolution and adaptation. Detection of functional orthologs using standard global sequence similarity methods faces several problems; the need for defining arbitrary acceptance thresholds for similarity and alignment length, lateral gene acquisition and the high computational cost for finding bi-directional best matches at a large scale. We investigated the use of protein domain architectures for large scale functional comparative analysis as an alternative method. The performance of both approaches was assessed through functional comparison of 446 bacterial genomes sampled at different taxonomic levels. We show that protein domain architectures provide a fast and efficient alternative to methods based on sequence similarity to identify groups of functionally equivalent proteins within and across taxonomic boundaries, and it is suitable for large scale comparative analysis. Running both methods in parallel pinpoints potential functional adaptations that may add to bacterial fitness.

Indexed as

Bacterial functionomeBacterial genomicsclusteringHorizontal gene transferOrthologysemantic annotation

Identifiers

PMID27703668
PMCPMC5031134

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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.