Evidence map›Paper›PMID 19776645›Full record

ReviewJournal of molecular microbiology and biotechnology2009

Bioinformatic analyses of transmembrane transport: novel software for deducing protein phylogeny, topology, and evolution.

Ming Ren Yen, Jeehye Choi, Milton H Saier

Abstract readReview
In one paragraph

Review in Journal of molecular microbiology and biotechnology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Article
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  5. Characterization of the Tetraspan Junctional Complex (4JC) superfamily.Biochimica et biophysica acta. Biomembranes · 2017
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  11. Amino acid uptake in rust fungi.Frontiers in plant science · 2015
    Article
  12. Article
  13. Article
  14. Article
  15. The transporter classification database.Nucleic acids research · 2014
    Article
  16. Article
  17. Article
  18. Arginine oscillation explains Na+ independence in the substrate/product antiporter CaiT.Proceedings of the National Academy of Sciences of the United States of America · 2013
    Article
  19. Article
  20. 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

3 authors.

Ming Ren YenDivision of Biological Sciences, University of California at San Diego, La Jolla, CA 92093-0116, USA.
Jeehye Choi
Milton H Saier

Funding

NIGMS NIH HHS GM1077402
6 · The paper itself

Abstract

During the past decade, we have experienced a revolution in the biological sciences resulting from the flux of information generated by genome-sequencing efforts. Our understanding of living organisms, the metabolic processes they catalyze, the genetic systems encoding cellular protein and stable RNA constituents, and the pathological conditions caused by some of these organisms has greatly benefited from the availability of complete genomic sequences and the establishment of comprehensive databases. Many research institutes around the world are now devoting their efforts largely to genome sequencing, data collection and data analysis. In this review, we summarize tools that are in routine use in our laboratory for characterizing transmembrane transport systems. Applications of these tools to specific transporter families are presented. Many of the computational approaches described should be applicable to virtually all classes of proteins and RNA molecules.

Indexed as

Evolution, MolecularPhylogenySoftwareBase SequenceComputational BiologyMembrane Transport ProteinsMolecular Sequence DataMembrane Transport Proteins

Identifiers

PMID19776645
PMCPMC2814153

What OpenQuestion holds

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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.