Your browser doesn't support javascript.
loading
MIAMI--a tool for non-targeted detection of metabolic flux changes for mode of action identification.
Dudek, Christian-Alexander; Reuse, Carsten; Fuchs, Regine; Hendriks, Janneke; Starck, Veronique; Hiller, Karsten.
Afiliação
  • Dudek CA; Department of Bioinformatics and Biochemistry, Technische Universität Braunschweig, Braunschweig 38106, Germany.
  • Reuse C; Department of Bioinformatics and Biochemistry, Technische Universität Braunschweig, Braunschweig 38106, Germany.
  • Fuchs R; BASF Metabolome Solutions GmbH, Berlin 10589, Germany.
  • Hendriks J; BASF Metabolome Solutions GmbH, Berlin 10589, Germany.
  • Starck V; BASF Metabolome Solutions GmbH, Berlin 10589, Germany.
  • Hiller K; BASF SE, Lampertheim 68623, Germany.
Bioinformatics ; 36(12): 3925-3926, 2020 06 01.
Article em En | MEDLINE | ID: mdl-32324861
ABSTRACT

SUMMARY:

Mass isotopolome analysis for mode of action identification (MIAMI) combines the strengths of targeted and non-targeted approaches to detect metabolic flux changes in gas chromatography/mass spectrometry datasets. Based on stable isotope labeling experiments, MIAMI determines a mass isotopomer distribution-based (MID) similarity network and incorporates the data into metabolic reference networks. By identifying MID variations of all labeled compounds between different conditions, targets of metabolic changes can be detected. AVAILABILITY AND IMPLEMENTATION We implemented the data processing in C++17 with Qt5 back-end using MetaboliteDetector and NTFD libraries. The data visualization is implemented as web application. Executable binaries and visualization are freely available for Linux operating systems, the source code is licensed under General Public License version 3.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Redes e Vias Metabólicas Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Redes e Vias Metabólicas Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article