Evidence map›Paper›PMID 28150250›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2017

Annotation of Alternatively Spliced Proteins and Transcripts with Protein-Folding Algorithms and Isoform-Level Functional Networks.

Hongdong Li, Yang Zhang, Yuanfang Guan, Rajasree Menon, Gilbert S Omenn

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Hongdong LiInstitute for Systems Biology, Seattle, WA, 98109, USA.
Yang ZhangDepartment of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Yuanfang GuanDepartment of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Rajasree MenonDepartment of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Gilbert S OmennDepartment of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA.

Funding

I-TASSER based atomic-level protein structure predictionR01GM083107 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, YANG · 2008 to 2019
$3.5M
Template-based docking refinement approach to protein-protein structure modelingR01GM116960 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, YANG · 2016 to 2019
$1.4M
NIGMS NIH HHS R01 GM083107NIGMS NIH HHS R01 GM116960
6 · The paper itself

Abstract

Tens of thousands of splice isoforms of proteins have been catalogued as predicted sequences from transcripts in humans and other species. Relatively few have been characterized biochemically or structurally. With the extensive development of protein bioinformatics, the characterization and modeling of isoform features, isoform functions, and isoform-level networks have advanced notably. Here we present applications of the I-TASSER family of algorithms for folding and functional predictions and the IsoFunc, MIsoMine, and Hisonet data resources for isoform-level analyses of network and pathway-based functional predictions and protein-protein interactions. Hopefully, predictions and insights from protein bioinformatics will stimulate many experimental validation studies.

Indexed as

AlgorithmsAlternative SplicingProtein FoldingProtein IsoformsAnimalsComputational BiologyGenome-Wide Association StudyHumansMiceModels, MolecularMolecular Sequence AnnotationProtein ConformationProteinsQuantitative Structure-Activity RelationshipSoftwareWeb BrowserProtein IsoformsProteinsFunctional predictionIsoform networkProtein foldingSplice isoforms

Identifiers

PMID28150250
PMCPMC5967847

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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.