Evidence map›Paper›PMID 25885037›Full record

ArticleBMC bioinformatics2015

Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource.

Scott Schuette, Brian Piatkowski, Aaron Corley, Daniel Lang, Matt Geisler

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
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

9 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
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  3. Review
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  5. Article
  6. Reconstruction and Application of Protein-Protein Interaction Network.International journal of molecular sciences · 2016
    Review
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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 at 2 institutions in 2 countries.

Scott SchuetteDepartment of Plant Biology, Southern Illinois University, Carbondale, IL, USA. swschuette@gmail.com.
Brian PiatkowskiDepartment of Plant Biology, Southern Illinois University, Carbondale, IL, USA. btpiatkowski@siu.edu.
Aaron CorleyDepartment of Plant Biology, Southern Illinois University, Carbondale, IL, USA. acorley101@gmail.com.
Daniel LangUniversity of Freiburg, Plant Biotechnology Schaenzlestr. 1, D-79104, Freiburg, Germany. daniel.lang@biologie.uni-freiburg.de.
Matt GeislerDepartment of Plant Biology, Southern Illinois University, Carbondale, IL, USA. mgeisler@plant.siu.edu.
Southern Illinois University Carbondale · USUniversity of Freiburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPhyscomitrella patens, a haploid dominant plant, is fast becoming a useful molecular genetics and bioinformatics tool due to its key phylogenetic position as a bryophyte in the post-genomic era. Genome sequences from select reference species were compared bioinformatically to Physcomitrella patens using reciprocal blasts with the InParanoid software package. A reference protein interaction database assembled using MySQL by compiling BioGrid, BIND, DIP, and Intact databases was queried for moss orthologs existing for both interacting partners. This method has been used to successfully predict interactions for a number of angiosperm plants.

resultsThe first predicted protein-protein interactome for a bryophyte based on the interolog method contains 67,740 unique interactions from 5,695 different Physcomitrella patens proteins. Most conserved interactions among proteins were those associated with metabolic processes. Over-represented Gene Ontology categories are reported here.

conclusionAddition of moss, a plant representative 200 million years diverged from angiosperms to interactomic research greatly expands the possibility of conducting comparative analyses giving tremendous insight into network evolution of land plants. This work helps demonstrate the utility of "guilt-by-association" models for predicting protein interactions, providing provisional roadmaps that can be explored using experimental approaches. Included with this dataset is a method for characterizing subnetworks and investigating specific processes, such as the Calvin-Benson-Bassham cycle.

Indexed as

Protein Interaction MappingAnimalsArabidopsisBryopsidaComputational BiologyGene OntologyGenome, PlantHumansMicePlant ProteinsRatsPlant Proteins

Identifiers

PMID25885037
PMCPMC4384322
OpenAlexW2098845490

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.