BAGEL4: a user-friendly web server to thoroughly mine RiPPs and bacteriocins

被引:648
|
作者
van Heel, Auke J. [1 ]
de Jong, Anne [1 ]
Song, Chunxu [1 ]
Viel, Jakob H. [1 ]
Kok, Jan [1 ]
Kuipers, Oscar P. [1 ]
机构
[1] Univ Groningen, Mol Genet, GBB, NL-9747 AG Groningen, Netherlands
基金
欧盟地平线“2020”;
关键词
CHEMICAL-STRUCTURES; PREDICTION; GENES;
D O I
10.1093/nar/gky383
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Interest in secondary metabolites such as RiPPs (ri-bosomally synthesized and posttranslationally modified peptides) is increasing worldwide. To facilitate the research in this field we have updated our mining web server. BAGEL4 is faster than its predecessor and is now fully independent from ORFcalling. Gene clusters of interest are discovered using the core-peptide database and/or through HMM motifs that are present in associated context genes. The databases used for mining have been updated and extended with literature references and links to UniProt and NCBI. Additionally, we have included automated promoter and terminator prediction and the option to upload RNA expression data, which can be displayed along with the identified clusters. Further improvements include the annotation of the context genes, which is now based on a fast blast against the prokaryote part of the UniRef90 database, and the improved web-BLAST feature that dynamically loads structural data such as internal cross-linking from UniProt. Overall BAGEL4 provides the user with more information through a user-friendly webinterface which simplifies data evaluation. BAGEL4 is freely accessible at http://bagel4.molgenrug.nl.
引用
收藏
页码:W278 / W281
页数:4
相关论文
共 50 条
  • [31] TkAnim: a user-friendly cross-platform Web animation tool
    De Paoli, D
    WEB TECHNOLOGIES AND APPLICATIONS, 1998, : 25 - 32
  • [32] An effective and user-friendly web application for the collaborative analysis of steel joints
    Gracia, J.
    Bayo, E.
    ADVANCES IN ENGINEERING SOFTWARE, 2018, 119 : 60 - 67
  • [33] REVERSE: a user-friendly web server for analyzing next-generation sequencing data from in vitro selection/evolution experiments
    Weiss, Zoe
    DasGupta, Saurja
    NUCLEIC ACIDS RESEARCH, 2022, 50 (W1) : W639 - W650
  • [34] PDB-tools web: A user-friendly interface for the manipulation of PDB files
    Jimenez-Garcia, Brian
    Teixeira, Joao M. C.
    Trellet, Mikael
    Rodrigues, Joao P. G. L. M.
    Bonvin, Alexandre M. J. J.
    PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2021, 89 (03) : 330 - 335
  • [35] spatialGE Is a User-Friendly Web Application That Facilitates Spatial Transcriptomics Data Analysis
    Ospina, Oscar E.
    Manjarres-Betancur, Roberto
    Gonzalez-Calderon, Guillermo
    Soupir, Alex C.
    Smalley, Inna
    Tsai, Kenneth Y.
    Markowitz, Joseph
    Khaled, Mariam L.
    Vallebuona, Ethan
    Berglund, Anders E.
    Eschrich, Steven A.
    Yu, Xiaoqing
    Fridley, Brooke L.
    CANCER RESEARCH, 2025, 85 (05) : 848 - 858
  • [36] An integrated user-friendly web-based spatial platform for bioenergy planning
    Tauro, Raul
    Rangel, Roberto
    Suarez, Rodrigo
    Luis Caballero, Jose
    Anaya-Merchant, Carlos
    Salinas-Melgoza, Miguel
    Guzman, Hector
    Ghilardi, Adrian
    BIOMASS & BIOENERGY, 2021, 145
  • [37] User-Friendly Locations of Error Messages in Web Forms: An Eye Tracking Study
    Inal, Yavuz
    JOURNAL OF EYE MOVEMENT RESEARCH, 2016, 9 (05):
  • [38] Nestedness for Dummies (NeD): A User-Friendly Web Interface for Exploratory Nestedness Analysis
    Strona, Giovanni
    Galli, Paolo
    Seveso, Davide
    Montano, Simone
    Fattorini, Simone
    JOURNAL OF STATISTICAL SOFTWARE, 2014, 59 (CS3): : 1 - 9
  • [39] amica: an interactive and user-friendly web-platform for the analysis of proteomics data
    Sebastian Didusch
    Moritz Madern
    Markus Hartl
    Manuela Baccarini
    BMC Genomics, 23
  • [40] A User-Friendly Web Tool for Custom Analysis of Continuous Glucose Monitoring Data
    Russon, Catherine L.
    Allen, Michael J.
    Pulsford, Richard M.
    Saunby, Michael
    Vaughan, Neil
    Cocks, Matthew
    Hesketh, Katie L.
    Low, Jonathan
    Andrews, Robert C.
    JOURNAL OF DIABETES SCIENCE AND TECHNOLOGY, 2024,