Evidence map›Paper›PMID 27017950›Full record

ArticlePeerJ2016

NeisseriaBase: a specialised Neisseria genomic resource and analysis platform.

Wenning Zheng, Naresh V R Mutha, Hamed Heydari, Avirup Dutta, Cheuk Chuen Siow, Nicholas S Jakubovics, Wei Yee Wee, Shi Yang Tan, Mia Yang Ang, Guat Jah Wong and 1 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 99% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

11 authors at 3 institutions in 3 countries.

Wenning ZhengDepartment of Oral Biology and Biomedical Sciences, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia; Genome Informatics Research Laboratory, HIR Building, University of Malaya, Kuala Lumpur, Malaysia.
Naresh V R MuthaGenome Informatics Research Laboratory, HIR Building, University of Malaya , Kuala Lumpur , Malaysia.
Hamed HeydariGenome Informatics Research Laboratory, HIR Building, University of Malaya, Kuala Lumpur, Malaysia; Computer Science and Engineering Department, University of NE-Lincoln, Lincoln NE, United States of America.
Avirup DuttaGenome Informatics Research Laboratory, HIR Building, University of Malaya , Kuala Lumpur , Malaysia.
Cheuk Chuen SiowGenome Informatics Research Laboratory, HIR Building, University of Malaya , Kuala Lumpur , Malaysia.
Nicholas S JakubovicsCentre for Oral Health Research, School of Dental Sciences, Newcastle University , Newcastle upon Tyne , United Kingdom.
Wei Yee WeeDepartment of Oral Biology and Biomedical Sciences, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia; Genome Informatics Research Laboratory, HIR Building, University of Malaya, Kuala Lumpur, Malaysia.
Shi Yang TanDepartment of Oral Biology and Biomedical Sciences, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia; Genome Informatics Research Laboratory, HIR Building, University of Malaya, Kuala Lumpur, Malaysia.
Mia Yang AngDepartment of Oral Biology and Biomedical Sciences, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia; Genome Informatics Research Laboratory, HIR Building, University of Malaya, Kuala Lumpur, Malaysia.
Guat Jah WongDepartment of Oral Biology and Biomedical Sciences, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia; Genome Informatics Research Laboratory, HIR Building, University of Malaya, Kuala Lumpur, Malaysia.
Siew Woh ChooDepartment of Oral Biology and Biomedical Sciences, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia; Genome Informatics Research Laboratory, HIR Building, University of Malaya, Kuala Lumpur, Malaysia; Genome Solutions Sdn Bhd, Suite 8, Innovation Incubator UM, Level 5, Research Management & Innovation Complex, University of Malaya, Kuala Lumpur, Malaysia.
University of Malaya · MYNewcastle University · GBUniversity of Nebraska–Lincoln · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background. The gram-negative Neisseria is associated with two of the most potent human epidemic diseases: meningococcal meningitis and gonorrhoea. In both cases, disease is caused by bacteria colonizing human mucosal membrane surfaces. Overall, the genus shows great diversity and genetic variation mainly due to its ability to acquire and incorporate genetic material from a diverse range of sources through horizontal gene transfer. Although a number of databases exist for the Neisseria genomes, they are mostly focused on the pathogenic species. In this present study we present the freely available NeisseriaBase, a database dedicated to the genus Neisseria encompassing the complete and draft genomes of 15 pathogenic and commensal Neisseria species. Methods. The genomic data were retrieved from National Center for Biotechnology Information (NCBI) and annotated using the RAST server which were then stored into the MySQL database. The protein-coding genes were further analyzed to obtain information such as calculation of GC content (%), predicted hydrophobicity and molecular weight (Da) using in-house Perl scripts. The web application was developed following the secure four-tier web application architecture: (1) client workstation, (2) web server, (3) application server, and (4) database server. The web interface was constructed using PHP, JavaScript, jQuery, AJAX and CSS, utilizing the model-view-controller (MVC) framework. The in-house developed bioinformatics tools implemented in NeisseraBase were developed using Python, Perl, BioPerl and R languages. Results. Currently, NeisseriaBase houses 603,500 Coding Sequences (CDSs), 16,071 RNAs and 13,119 tRNA genes from 227 Neisseria genomes. The database is equipped with interactive web interfaces. Incorporation of the JBrowse genome browser in the database enables fast and smooth browsing of Neisseria genomes. NeisseriaBase includes the standard BLAST program to facilitate homology searching, and for Virulence Factor Database (VFDB) specific homology searches, the VFDB BLAST is also incorporated into the database. In addition, NeisseriaBase is equipped with in-house designed tools such as the Pairwise Genome Comparison tool (PGC) for comparative genomic analysis and the Pathogenomics Profiling Tool (PathoProT) for the comparative pathogenomics analysis of Neisseria strains. Discussion. This user-friendly database not only provides access to a host of genomic resources on Neisseria but also enables high-quality comparative genome analysis, which is crucial for the expanding scientific community interested in Neisseria research. This database is freely available at http://neisseria.um.edu.my.

Indexed as

Comparative analysisGenomic resourcesNeisseriaNeisseriaBasePairwise Genome Comparison toolPathogenomics Profiling tool

Identifiers

PMID27017950
PMCPMC4806638
OpenAlexW2302139914

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.