ArticleJournal of bioinformatics and computational biology2012
A new metabolomics analysis technique: steady-state metabolic network dynamics analysis.
Article in Journal of bioinformatics and computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Cell energy metabolism and bone formation.Bone reports · 2022Article
- From metabolomics to fluxomics: a computational procedure to translate metabolite profiles into metabolic fluxes.Biophysical journal · 2015Article
- MIRA: mutual information-based reporter algorithm for metabolic networks.Bioinformatics (Oxford, England) · 2014Article
- An online system for metabolic network analysis.Database : the journal of biological databases and curation · 2014Article
- ADEMA: an algorithm to determine expected metabolite level alterations using mutual information.PLoS computational biology · 2013Article
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Authors and funding
7 authors.
Funding
Abstract
With the recent advances in experimental technologies, such as gas chromatography and mass spectrometry, the number of metabolites that can be measured in biofluids of individuals has markedly increased. Given a set of such measurements, a very common task encountered by biologists is to identify the metabolic mechanisms that lead to changes in the concentrations of given metabolites and interpret the metabolic consequences of the observed changes in terms of physiological problems, nutritional deficiencies, or diseases. In this paper, we present the steady-state metabolic network dynamics analysis (SMDA) approach in detail, together with its application in a cystic fibrosis study. We also present a computational performance evaluation of the SMDA tool against a mammalian metabolic network database. The query output space of the SMDA tool is exponentially large in the number of reactions of the network. However, (i) larger numbers of observations exponentially reduce the output size, and (ii) exploratory search and browsing of the query output space is provided to allow users to search for what they are looking for.
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