Planning optimal measurements of isotopomer distributions for estimation of metabolic fluxes
| Autor: | Taneli Mielikäinen, Ari Rantanen, Esko Ukkonen, Hannu Maaheimo, Juho Rousu |
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| Jazyk: | angličtina |
| Rok vydání: | 2006 |
| Předmět: |
0106 biological sciences
Optimization problem Magnetic Resonance Spectroscopy Computational complexity theory Computer science Metabolite Metabolic network Bioinformatics computer.software_genre Central carbon metabolism 01 natural sciences Biochemistry Mass Spectrometry Isotopomers chemistry.chemical_compound metabolic flux analysis Metabolic flux analysis Protein Interaction Mapping metabolites 0303 health sciences Nuclear magnetic resonance spectroscopy metabolomics Computer Science Applications Computational Mathematics Computational Theory and Mathematics Data mining Signal transduction Algorithms Signal Transduction Statistics and Probability Saccharomyces cerevisiae Proteins Saccharomyces cerevisiae isotopomer distribution Mass spectrometry Models Biological 03 medical and health sciences Metabolomics 010608 biotechnology Computer Simulation Molecular Biology 030304 developmental biology Estimation Measure (data warehouse) metabolic profiling Carbon Metabolic pathway chemistry Informatics computer Diagnostic Techniques Radioisotope |
| Zdroj: | Rantanen, A, Mielikäinen, T, Rousu, J, Maaheimo, H & Ukkonen, E 2006, ' Planning optimal measurements of isotopomer distributions for estimation of metabolic fluxes ', Bioinformatics, vol. 22, no. 10, pp. 1198-1206 . https://doi.org/10.1093/bioinformatics/btl069 |
| DOI: | 10.1093/bioinformatics/btl069 |
| Popis: | Motivation: Flux estimation using isotopomer information of metabolites is currently the most reliable method to obtain quantitative estimates of the activity of metabolic pathways. However, the development of isotopomer measurement techniques for intermediate metabolites is a demanding task. Careful planning of isotopomer measurements is thus needed to maximize the available flux information while minimizing the experimental effort. Results: In this paper we study the question of finding the smallest subset of metabolites to measure that ensure the same level of isotopomer information as the measurement of every metabolite in the metabolic network. We study the computational complexity of this optimization problem in the case of the so-called positional enrichment data, give methods for obtaining exact and fast approximate solutions, and evaluate empirically the efficacy of the proposed methods by analyzing a metabolic network that models the central carbon metabolism of Saccharomyces cerevisiae. Contact: ajrantan@cs.helsinki.fi |
| Databáze: | OpenAIRE |
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