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PMAnalyzer: a new web interface for bacterial growth curve analysis.
Cuevas, Daniel A; Edwards, Robert A.
Afiliación
  • Cuevas DA; Computational Science Research Center, San Diego State University, San Diego, CA, USA.
  • Edwards RA; Computational Science Research Center, San Diego State University, San Diego, CA, USA.
Bioinformatics ; 33(12): 1905-1906, 2017 Jun 15.
Article en En | MEDLINE | ID: mdl-28200078
SUMMARY: Bacterial growth curves are essential representations for characterizing bacteria metabolism within a variety of media compositions. Using high-throughput, spectrophotometers capable of processing tens of 96-well plates, quantitative phenotypic information can be easily integrated into the current data structures that describe a bacterial organism. The PMAnalyzer pipeline performs a growth curve analysis to parameterize the unique features occurring within microtiter wells containing specific growth media sources. We have expanded the pipeline capabilities and provide a user-friendly, online implementation of this automated pipeline. PMAnalyzer version 2.0 provides fast automatic growth curve parameter analysis, growth identification and high resolution figures of sample-replicate growth curves and several statistical analyses. AVAILABILITY AND IMPLEMENTATION: PMAnalyzer v2.0 can be found at https://edwards.sdsu.edu/pmanalyzer/ . Source code for the pipeline can be found on GitHub at https://github.com/dacuevas/PMAnalyzer . Source code for the online implementation can be found on GitHub at https://github.com/dacuevas/PMAnalyzerWeb . CONTACT: dcuevas08@gmail.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Bacterias / Programas Informáticos / Biología Computacional Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Bacterias / Programas Informáticos / Biología Computacional Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos