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KiPar, a tool for systematic information retrieval regarding parameters for kinetic modelling of yeast metabolic pathways
Author(s) -
‪Irena Spasić,
Evangelos Simeonidis,
Hanan L. Messiha,
Norman W. Paton,
Douglas B. Kell
Publication year - 2009
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btp175
Subject(s) - computer science , terminology , identifier , context (archaeology) , information retrieval , search engine indexing , data mining , software , pairwise comparison , data science , modularity (biology) , artificial intelligence , biology , paleontology , philosophy , linguistics , genetics , programming language
Most experimental evidence on kinetic parameters is buried in the literature, whose manual searching is complex, time consuming and partial. These shortcomings become particularly acute in systems biology, where these parameters need to be integrated into detailed, genome-scale, metabolic models. These problems are addressed by KiPar, a dedicated information retrieval system designed to facilitate access to the literature relevant for kinetic modelling of a given metabolic pathway in yeast. Searching for kinetic data in the context of an individual pathway offers modularity as a way of tackling the complexity of developing a full metabolic model. It is also suitable for large-scale mining, since multiple reactions and their kinetic parameters can be specified in a single search request, rather than one reaction at a time, which is unsuitable given the size of genome-scale models.

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