Journalartikel

Autorenliste: Goesmann, A; Haubrock, M; Meyer, F; Kalinowski, J; Giegerich, R

Jahr der Veröffentlichung: 2002

Seiten: 124-129

Zeitschrift: Bioinformatics

Bandnummer: 18

Heftnummer: 1

ISSN: 1367-4803

eISSN: 1460-2059

DOI Link: https://doi.org/10.1093/bioinformatics/18.1.124

Verlag: Oxford University Press

Abstract: 
Motivation: Beyond methods for a gene-wise annotation and analysis of sequenced genomes new automated methods for functional analysis on a higher level are needed. The identification of realized metabolic pathways provides valuable information on gene expression and regulation. Detection of incomplete pathways helps to improve a constantly evolving genome annotation or discover alternative biochemical pathways. To utilize automated genome analysis on the level of metabolic pathways new methods for the dynamic representation and visualization of pathways are needed.Results: PathFinder is a tool for the dynamic visualization of metabolic pathways based on annotation data. Pathways are represented as directed acyclic graphs, graph layout algorithms accomplish the dynamic drawing and visualization of the metabolic maps. A more detailed analysis of the input data on the level of biochemical pathways helps to identify genes and detect improper parts of annotations. As an Relational Database Management System (RDBMS) based internet application PathFinder reads a list of EC-numbers or a given annotation in EMBL- or Genbank-format and dynamically generates pathway graphs.

Harvard-Zitierstil: Goesmann, A., Haubrock, M., Meyer, F., Kalinowski, J. and Giegerich, R. (2002) PathFinder: reconstruction and dynamic visualization of metabolic pathways, Bioinformatics, 18(1), pp. 124-129. https://doi.org/10.1093/bioinformatics/18.1.124

APA-Zitierstil: Goesmann, A., Haubrock, M., Meyer, F., Kalinowski, J., & Giegerich, R. (2002). PathFinder: reconstruction and dynamic visualization of metabolic pathways. Bioinformatics. 18(1), 124-129. https://doi.org/10.1093/bioinformatics/18.1.124