Evidence map›Paper›PMID 28839186›Full record

ArticleNature communications2017

An integrated bioinformatics platform for investigating the human E3 ubiquitin ligase-substrate interaction network.

Yang Li, Ping Xie, Liang Lu, Jian Wang, Lihong Diao, Zhongyang Liu, Feifei Guo, Yangzhige He, Yuan Liu, Qin Huang and 3 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 158 papers.

0numbers the graph read from it
0cells of the map it votes in
158citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

158 citing papers in PubMed, 252 citations in OpenAlex.

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98 more citing papers are in PubMed but not listed here.

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

13 authors at 4 institutions in 2 countries.

Yang LiState Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, National Center for Protein Sciences (The PHOENIX Center, Beijing), Beijing, 102206, China.
Ping XieState Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, National Center for Protein Sciences (The PHOENIX Center, Beijing), Beijing, 102206, China.
Liang LuState Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, National Center for Protein Sciences (The PHOENIX Center, Beijing), Beijing, 102206, China.
Jian WangState Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, National Center for Protein Sciences (The PHOENIX Center, Beijing), Beijing, 102206, China.
Lihong DiaoState Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, National Center for Protein Sciences (The PHOENIX Center, Beijing), Beijing, 102206, China.
Zhongyang LiuState Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, National Center for Protein Sciences (The PHOENIX Center, Beijing), Beijing, 102206, China.
Feifei GuoState Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, National Center for Protein Sciences (The PHOENIX Center, Beijing), Beijing, 102206, China.
Yangzhige HeState Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, National Center for Protein Sciences (The PHOENIX Center, Beijing), Beijing, 102206, China.
Yuan LiuState Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, National Center for Protein Sciences (The PHOENIX Center, Beijing), Beijing, 102206, China.
Qin HuangSchool of Chemistry and Chemical Engineering, Guangxi University for Nationalities, Nanning, 530006, China.
Han LiangDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.ORCID 0000-0001-7633-286X
Dong LiState Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, National Center for Protein Sciences (The PHOENIX Center, Beijing), Beijing, 102206, China. lidong.bprc@foxmail.com.
Fuchu HeState Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, National Center for Protein Sciences (The PHOENIX Center, Beijing), Beijing, 102206, China. hefc@nic.bmi.ac.cn.
Beijing Proteome Research Center · CNGuangxi University for Nationalities · CNCapital Medical University · CNThe University of Texas MD Anderson Cancer Center · US

Funding

TCPA: an Integrated Bioinformatics Resource for Functional Cancer Proteomic DataU24CA209851 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LIANG, HAN, MILLS, GORDON B. · 2016 to 2020
$4.0M
Systematic Functional Characterization of RNA Editing in Endometrial CancerR01CA175486 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LIANG, HAN · 2014 to 2018
$1.7M
NCI NIH HHS R01 CA175486NCI NIH HHS U24 CA209851
6 · The paper itself

Abstract

The ubiquitination mediated by ubiquitin activating enzyme (E1), ubiquitin conjugating enzyme (E2), and ubiquitin ligase (E3) cascade is crucial to protein degradation, transcription regulation, and cell signaling in eukaryotic cells. The high specificity of ubiquitination is regulated by the interaction between E3 ubiquitin ligases and their target substrates. Unfortunately, the landscape of human E3-substrate network has not been systematically uncovered. Therefore, there is an urgent need to develop a high-throughput and efficient strategy to identify the E3-substrate interaction. To address this challenge, we develop a computational model based on multiple types of heterogeneous biological evidence to investigate the human E3-substrate interactions. Furthermore, we provide UbiBrowser as an integrated bioinformatics platform to predict and present the proteome-wide human E3-substrate interaction network ( http://ubibrowser.ncpsb.org ).Protein stability modulation by E3 ubiquitin ligases is an important layer of functional regulation, but screening for E3 ligase-substrate interactions is time-consuming and costly. Here, the authors take an in silico naïve Bayesian classifier approach to integrate multiple lines of evidence for E3-substrate prediction, enabling prediction of the proteome-wide human E3 ligase interaction network.

Indexed as

AlgorithmsProtein Interaction MapsBayes TheoremComputational BiologyHumansProtein BindingProteomeReproducibility of ResultsSubstrate SpecificityUbiquitinationUbiquitin-Conjugating EnzymesUbiquitin-Protein LigasesProteomeUbiquitin-Conjugating EnzymesUbiquitin-Protein Ligases

Identifiers

PMID28839186
PMCPMC5570908
OpenAlexW2745944099

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.