Evidence map›Paper›PMID 33680357›Full record

ReviewComputational and structural biotechnology journal2021

Protein domain identification methods and online resources.

Yan Wang, Hang Zhang, Haolin Zhong, Zhidong Xue

Abstract readReview
In one paragraph

Review in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

44 citing papers in PubMed.

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  18. Order of amino acid recruitment into the genetic code resolved by last universal common ancestor's protein domains.Proceedings of the National Academy of Sciences of the United States of America · 2024
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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

4 authors.

Yan WangInstitute of Medical Artificial Intelligence, Binzhou Medical College, Yantai, Shandong 264003, China.
Hang ZhangSchool of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
Haolin ZhongSchool of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
Zhidong XueSchool of Software Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein domains are the basic units of proteins that can fold, function, and evolve independently. Knowledge of protein domains is critical for protein classification, understanding their biological functions, annotating their evolutionary mechanisms and protein design. Thus, over the past two decades, a number of protein domain identification approaches have been developed, and a variety of protein domain databases have also been constructed. This review divides protein domain prediction methods into two categories, namely sequence-based and structure-based. These methods are introduced in detail, and their advantages and limitations are compared. Furthermore, this review also provides a comprehensive overview of popular online protein domain sequence and structure databases. Finally, we discuss potential improvements of these prediction methods.

Indexed as

Artificial reefMixSIARNatural reefStable isotopesTrophic pathwayTrophic structure

Identifiers

PMID33680357
PMCPMC7895673

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.