Evidence map›Paper›PMID 30419809›Full record

ArticleBMC bioinformatics2018

WebNetCoffee: a web-based application to identify functionally conserved proteins from Multiple PPI networks.

Jialu Hu, Yiqun Gao, Junhao He, Yan Zheng, Xuequn Shang

Abstract read
In one paragraph

Article in BMC bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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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.

Jialu HuSchool of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, China.
Yiqun GaoSchool of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, China.
Junhao HeSchool of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, China.
Yan ZhengSchool of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, China.
Xuequn ShangSchool of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, China. shang@nwpu.edu.cn.

Funding

National Natural Science Foundation of China 61332014National Natural Science Foundation of China 61702420National Natural Science Foundation of China 61772426Postdoctoral Research Foundation of China 2017M613203
6 · The paper itself

Abstract

backgroundThe discovery of functionally conserved proteins is a tough and important task in system biology. Global network alignment provides a systematic framework to search for these proteins from multiple protein-protein interaction (PPI) networks. Although there exist many web servers for network alignment, no one allows to perform global multiple network alignment tasks on users' test datasets.

resultsHere, we developed a web server WebNetcoffee based on the algorithm of NetCoffee to search for a global network alignment from multiple networks. To build a series of online test datasets, we manually collected 218,339 proteins, 4,009,541 interactions and many other associated protein annotations from several public databases. All these datasets and alignment results are available for download, which can support users to perform algorithm comparison and downstream analyses.

conclusionWebNetCoffee provides a versatile, interactive and user-friendly interface for easily running alignment tasks on both online datasets and users' test datasets, managing submitted jobs and visualizing the alignment results through a web browser. Additionally, our web server also facilitates graphical visualization of induced subnetworks for a given protein and its neighborhood. To the best of our knowledge, it is the first web server that facilitates the performing of global alignment for multiple PPI networks. AVAILABILITY: http://www.nwpu-bioinformatics.com/WebNetCoffee.

Indexed as

Computational BiologyHumansProtein Interaction MappingGene ontologyMultiple network alignmentPPI networksProtein databasesWebserver

Identifiers

PMID30419809
PMCPMC6233501

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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.