Chapter 10: Perturbations to metabolic networks #
Fast-SL: an efficient algorithm to identify synthetic lethal sets in metabolic networks
Pratapa et al. (2015) BioinformaticsDescribes a novel and rapid method for identifying synthetic lethals in metabolic networks, by cutting through the search space.
Genome-scale gene/reaction essentiality and synthetic lethality analysis
Suthers et al. (2009) Molecular Systems BiologyDescribes SL-Finder, an MILP-based method to identify synthetic lethals.
Enumeration of Smallest Intervention Strategies in Genome-Scale Metabolic Networks
von Kamp and Klamt (2014) PLoS Computational BiologyDescribes MCSEnumerator, an efficient MILP-based method to identify synthetic lethals.
Global reconstruction of the human metabolic network based on genomic and bibliomic data
Duarte et al. (2007) Proceedings of the National Academy of Sciences USAThe classic reconstruction of human metabolic network, ““Recon 1
A community-driven global reconstruction of human metabolism
Thiele et al. (2013) Nature biotechnologyThe Recon 2 human metabolic model.
Computational reconstruction of tissue-specific metabolic models: application to human liver metabolism
Jerby et al. (2010) Molecular Systems BiologyTissue-specific metabolic reconstruction.
Insight into human alveolar macrophage and M. tuberculosis interactions via metabolic reconstructions
Bordbar et al. (2010) Molecular Systems BiologyModelling host–pathogen interactions using metabolic modelling.
A multi-tissue type genome-scale metabolic network for analysis of whole-body systems physiology
Bordbar et al. (2011) BMC Systems BiologyTissue-specific metabolic reconstruction, for Recon 1, modelling adipocytes, hepatocytes, and myocytes.
Reconstruction of Genome-Scale Active Metabolic Networks for 69 Human Cell Types and 16 Cancer Types Using INIT
Agren et al. (2012) PLoS Computational BiologyExcellent example of context-specific metabolic reconstructions.
Predicting selective drug targets in cancer through metabolic networks
Folger et al. (2011) Molecular Systems BiologyThe first genome-scale metabolic model of cancer metabolism.
Large-scale in silico modeling of metabolic interactions between cell types in the human brain
Lewis et al. (2010) Nature BiotechnologyA workflow that integrates gene expression data, proteomics data and literature-based manual curation to model human metabolism within and between different types of cells.
A compendium of inborn errors of metabolism mapped onto the human metabolic network
Sahoo et al. (2012) Molecular bioSystemsA comprehensive knowledgebase of inborn errors of metabolism.
Predicting the impact of diet and enzymopathies on human small intestinal epithelial cells
Sahoo and Thiele (2013) Human Molecular GeneticsThis paper defined fifty metabolic tasks to evaluate model functionalities.
How Will Bioinformatics Influence Metabolic Engineering?
Edwards and Palsson (1997) Biotechnology and BioengineeringA classic review, discussing computational approaches for metabolic engineering.
Basic concepts and principles of stoichiometric modeling of metabolic networks
Maarleveld et al. (2013) Biotechnology JournalAn excellent review covering the breadth of metabolic modelling.
The Convex Basis of the Left Null Space of the Stoichiometric Matrix Leads to the Definition of Metabolically Meaningful Pools
Famili and Palsson (2003) Biophysical JournalA nice paper providing detailed insights into stoichiometric matrix and the convex basis of the metabolic solution spaces.
Systemic metabolic reactions are obtained by singular value decomposition of genome-scale stoichiometric matrices
Famili and Palsson (2003) Journal of Theoretical BiologySVD analysis of the stoichiometric matrix.
Constraining the metabolic genotype–phenotype relationship using a phylogeny of in silico methods
Lewis et al. (2012) Nature Reviews MicrobiologyA detailed review of the entire family of COBRA methods (with a beautiful method phylogeny picture).
Regulation of Gene Expression in Flux Balance Models of Metabolism
Covert et al. (2001) Journal of Theoretical BiologyThe classic paper on rFBA.
Interpreting Expression Data with Metabolic Flux Models: Predicting Mycobacterium tuberculosis Mycolic Acid Production
Colijn et al. (2009) PLoS Computational BiologyDescribes the E-Flux method for integration of regulatory information.
Probabilistic integrative modeling of genome-scale metabolic and regulatory networks in Escherichia coli and Mycobacterium tuberculosis
Chandrasekharan and Price (2010) Proceedings of the National Academy of Sciences USADescribes the PROM approach for integration of regulatory information from gene expression datasets.
Constraint-based models predict metabolic and associated cellular functions
Bordbar et al. (2014) Nature Reviews GeneticsAn excellent review on constraint-based models and their applications.
Identifying gene targets for the metabolic engineering of lycopene biosynthesis in Escherichia coli
Alper et al. (2005) Metabolic EngineeringA classic application of FBA for metabolic engineering, including identification of a triple knock-out for improving lycopene production.
Flux Balance Analysis of Mycolic Acid Pathway: Targets for Anti-Tubercular Drugs
Raman et al. (2005) PLoS Computational BiologyA classic application of FBA for drug target identification by modelling the mycolic acid pathway in Mycobacterium tuberculosis.
targetTB: A target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis
Raman et al. (2008) BMC Systems BiologyA rigorous pipeline for drug target identification in Mycobacterium tuberculosis.
Applications of genome-scale metabolic reconstructions
Oberhardt et al. (2009) Molecular Systems BiologyA detailed review, discussing various classes of applications of constraint-based modelling.
The application of flux balance analysis in systems biology
Gianchandani et al. (2010) Wiley Interdisciplinary Reviews: Systems Biology and MedicineA nice and simple overview of FBA and related methods, with applications.
Genome-scale metabolic networks
Terzer et al. (2009) Wiley Interdisciplinary Reviews: Systems Biology and MedicineA very nice review on various aspects of metabolic network reconstruction and simulation.
Elementary flux modes in a nutshell: Properties, calculation and applications
Zanghellini et al. (2013) Biotechnology JournalA neat introduction to EFM analysis, using a ““metro map”” analogy.
Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering
Schuster et al. (1999) Trends in BiotechnologyAn excellent paper on EFMs.
Elementary mode analysis: a useful metabolic pathway analysis tool for characterizing cellular metabolism
Trinh et al. (2009) Applied microbiology and biotechnologyA nice review detailing EFMs, especially their applications for metabolic engineering.
Comparison of network-based pathway analysis methods
Papin et al. (2004) Trends in BiotechnologyA neat illustration of EFM vs. EPA analyses.
On Elementary Flux Modes in Biochemical Reaction Systems at Steady State
Schuster and Hilgetag (1994) Journal of Biological SystemsThe classic paper on EFMs.
Extreme Pathway Analysis of Human Red Blood Cell Metabolism
Wiback and Palsson (2002) Biophysical journalDiscusses EPA, for studying human RBC metabolism.
High-throughput metabolic flux analysis based on gas chromatography�mass spectrometry derived 13C constraints
Fischer et al. (2004) Analytical BiochemistryA classic paper giving a clear rundown of 13C-MFA.
13C Metabolic Flux Analysis
Wiechert (2001) Metabolic EngineeringA classic review on 13C-MFA.
13C-based metabolic flux analysis
Zamboni et al. (2009) Nature ProtocolsA detailed protocol paper elucidating the 13C-MFA approach.
How to measure metabolic fluxes: a taxonomic guide for 13C fluxomics
Niedenfuehr et al. (2015) Current Opinion in BiotechnologyAnother excellent review on 13C-MFA.
13C Metabolic Flux Analysis for Systematic Metabolic Engineering of S. cerevisiae for Overproduction of Fatty Acids
Ghosh et al. (2016) Frontiers in Bioengineering and BiotechnologyA nice illustration of flux analysis for improving production of fatty acids in yeast.