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001			233851
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007			cr nn 008mamaa
008			130217s2013 xxu| s |||| 0|eng d
020			_a9781627032995
024	7		_a10.1007/978-1-62703-299-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
245	1	0	_aSystems Metabolic Engineering _bMethods and Protocols _cedited by Hal S. Alper.
250			_a1st edition 2013
264		1	_aTotowa, NJ _bHumana Press _c2013
300			_a1 recurso en línea (XII, 474 páginas) _b61 ilustraciones, 47 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aMethods in Molecular Biology _x1940-6029
505	0		_aGenome-Scale Model Management and Comparison -- Automated Genome Annotation and Metabolic Model Reconstruction in the SEED and Model SEED -- Metabolic Model Refinement Using Phenotypic Microarray Data -- Linking Genome-Scale Metabolic Modeling and Genome Annotation -- Resolving Cell Composition through Simple Measurements, Genome-Scale Modeling, and a Genetic Algorithm -- A Guide to Integrating Transcriptional Regulatory and Metabolic Networks Using PROM (Probabilistic Regulation of Metabolism) -- Kinetic Modeling of Metabolic Pathways: Application to Serine Biosynthesis -- Computational Tools for Guided Discovery and Engineering of Metabolic Pathways -- Retrosynthetic Design of Heterologous Pathways -- Customized Optimization of Metabolic Pathways by Combinatorial Transcriptional Engineering -- Adaptive Laboratory Evolution for Strain Engineering -- Trackable Multiplex Recombineering for Gene-Trait Mapping in E. coli -- Identification of Mutations in Evolved Bacterial Genomes -- Discovery of Post-Transcriptional Regulatory RNAs Using Next Generation Sequencing Technologies -- 13C-based Metabolic Flux Analysis: Fundamentals and Practice -- Nuclear Magnetic Resonance Methods for Metabolic Fluxomics -- Using Multiple Tracers for 13C Metabolic Flux Analysis -- Isotopically Nonstationary 13C Metabolic Flux Analysis -- Sample Preparation and Biostatistics for Integrated Genomics Approaches -- Targeted Metabolic Engineering Guided by Computational Analysis of Single Nucleotide Polymorphisms (SNPs) -- Linking RNA Measurements and Proteomics with Genome-Scale Models -- Comparative Transcriptome Analysis for Metabolic Engineering -- Merging Multiple Omics Datasets In Silico: Statistical Analyses and Data Interpretation.
520			_aWith the ultimate goal of systematically and robustly defining the specific perturbations necessary to alter a cellular phenotype, systems metabolic engineering has the potential to lead to a complete cell model capable of simulating cell and metabolic function as well as predicting phenotypic response to changes in media, gene knockouts/overexpressions, or the incorporation of heterologous pathways.  In Systems Metabolic Engineering: Methods and Protocols, experts in the field describe the methodologies and approaches in the area of systems metabolic engineering and provide a step-by-step guide for their implementation. Four major tenants of this approach are addressed, including modeling and simulation, multiplexed genome engineering, 'omics technologies, and large data-set incorporation and synthesis, all elucidated through the use of model host organisms.  Written in the highly successful Methods in Molecular Biology™ series format, chapters include introductions on their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.   Comprehensive and cutting-edge, Systems Metabolic Engineering: Methods and Protocols serves as an ideal guide for metabolic engineers, molecular biologists, and microbiologists aiming to implement the most recent approaches available in the field.
700	1		_aAlper, Hal S _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9781627032988
776	0	8	_iPrinted edition: _z9781627033008
776	0	8	_iPrinted edition: _z9781493962921
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-62703-299-5 _z(usuarios Universidad Europea de Valencia)
942			_2lcc _cLE
988			_aSpringer_Protocols_2013
999			_c233851 _d233851