Prediction of metabolic fluxes from gene expression data with Huber penalty convex optimization function
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Title
Prediction of metabolic fluxes from gene expression data with Huber penalty convex optimization function
Authors
Keywords
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Journal
Molecular BioSystems
Volume 13, Issue 5, Pages 901-909
Publisher
Royal Society of Chemistry (RSC)
Online
2017-03-14
DOI
10.1039/c6mb00811a
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- (2016) Min Kyung Kim et al. PLoS One
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- (2015) Maciek R. Antoniewicz JOURNAL OF INDUSTRIAL MICROBIOLOGY & BIOTECHNOLOGY
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- (2014) Aarash Bordbar et al. NATURE REVIEWS GENETICS
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- Systematic Evaluation of Methods for Integration of Transcriptomic Data into Constraint-Based Models of Metabolism
- (2014) Daniel Machado et al. PLoS Computational Biology
- Methods for integration of transcriptomic data in genome-scale metabolic models
- (2014) Min Kyung Kim et al. Computational and Structural Biotechnology Journal
- Improving metabolic flux predictions using absolute gene expression data
- (2012) Dave Lee et al. BMC Systems Biology
- Yeast 5 – an expanded reconstruction of the Saccharomyces cerevisiae metabolic network
- (2012) Benjamin D Heavner et al. BMC Systems Biology
- Cellular Metabolism and Disease: What Do Metabolic Outliers Teach Us?
- (2012) Ralph J. DeBerardinis et al. CELL
- Analysis of omics data with genome-scale models of metabolism
- (2012) Daniel R. Hyduke et al. Molecular BioSystems
- Integration of expression data in genome-scale metabolic network reconstructions
- (2012) Anna S. Blazier et al. Frontiers in Physiology
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- (2011) A. Mardinoglu et al. JOURNAL OF INTERNAL MEDICINE
- iMAT: an integrative metabolic analysis tool
- (2010) Hadas Zur et al. BIOINFORMATICS
- Metabolic and Transcriptional Response to Cofactor Perturbations in Escherichia coli
- (2010) Anders K. Holm et al. JOURNAL OF BIOLOGICAL CHEMISTRY
- What is flux balance analysis?
- (2010) Jeffrey D Orth et al. NATURE BIOTECHNOLOGY
- A protocol for generating a high-quality genome-scale metabolic reconstruction
- (2010) Ines Thiele et al. Nature Protocols
- Flux balance analysis of biological systems: applications and challenges
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- (2008) Scott A. Becker et al. PLoS Computational Biology
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