Evidence map›Paper›PMID 28167677›Full record

ReviewBioscience reports2017

Computational approaches for

Gunseli Bayram Akcapinar, Osman Ugur Sezerman

Open access · goldAbstract readReview
In one paragraph

Review in Bioscience reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

16 citing papers in PubMed, 41 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Gunseli Bayram AkcapinarDepartment of Statistics and Medical Informatics, School of Medicine, Acibadem University, Istanbul, Turkey.
Osman Ugur SezermanDepartment of Statistics and Medical Informatics, School of Medicine, Acibadem University, Istanbul, Turkey Ugur.Sezerman@acibadem.edu.tr.
Acıbadem University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metal ions play pivotal roles in protein structure, function and stability. The functional and structural diversity of proteins in nature expanded with the incorporation of metal ions or clusters in proteins. Approximately one-third of these proteins in the databases contain metal ions. Many biological and chemical processes in nature involve metal ion-binding proteins, aka metalloproteins. Many cellular reactions that underpin life require metalloproteins. Most of the remarkable, complex chemical transformations are catalysed by metalloenzymes. Realization of the importance of metal-binding sites in a variety of cellular events led to the advancement of various computational methods for their prediction and characterization. Furthermore, as structural and functional knowledgebase about metalloproteins is expanding with advances in computational and experimental fields, the focus of the research is now shifting towards

Indexed as

Amino Acid MotifsBinding SitesComputational BiologyDatabases, ProteinHumansMetalloproteinsMetalsModels, MolecularProtein EngineeringMetalloproteinsMetalsartificial metalloproteinscomputational protein designcomputational protein re-designde novo designmetal binding sites

Identifiers

PMID28167677
PMCPMC5482196
OpenAlexW2586685672

What OpenQuestion holds

Textmetadata
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.