Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Engineering complex phenotypes in industrial strains [[electronic resource] /] / edited by Ranjan Patnaik
| Engineering complex phenotypes in industrial strains [[electronic resource] /] / edited by Ranjan Patnaik |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley, 2012 |
| Descrizione fisica | 1 online resource (290 p.) |
| Disciplina | 579/.163 |
| Altri autori (Persone) | PatnaikRanjan <1969-> |
| Soggetto topico |
Genetic engineering
Industrial microorganisms |
| ISBN |
1-118-43304-1
1-118-43303-3 1-283-64527-0 1-118-43300-9 |
| Classificazione | TEC009010 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Title page; Copyright page; Contents; Foreword; Preface; Contributors; 1: Classical Strain Improvement; 1.0 Introduction; 1.1 The Approach Defined; 1.2 Mutagenesis; 1.2.1 Numerical Considerations in Screen Design; 1.2.2 Random Genetic Drift; 1.2.3 Forced Mutagenesis; 1.2.4 Strain Mating; 1.3 Genotypic Landscapes; 1.4 Screening; 1.4.1 Rational Screens; 1.4.2 Random Screens; 1.4.3 Screening Platforms; 1.5 Conclusions; References; 2: Tracer-Based Analysis of Metabolic Flux Networks; 2.0 Introduction; 2.1 Setting Up a Stoichiometric Network Model; 2.2 Small-Scale Models versus Genome Scale Models
2.3 Network Analysis: Maximum Theoretical Yield2.4 (Stoichiometric) Metabolic Flux Analysis; 2.5 Carrying Out a Labeling Experiment; 2.6 MEASURING ISOTOPE LABELING PATTERNS; 2.7 Tracer-Based MFA; 2.8 Validating Metabolic Flux Networks; 2.9 Conclusions; Acknowledgments; References; 3: Integration of "Omics" Data with Genome-Scale Metabolic Models; 3.0 Introduction; 3.1 Genome-Scale Metabolic Networks; 3.2 Constraint-Based Modeling Theory; 3.3 Current Analysis of Omics Data; 3.4 New Approaches to Developing Model Constraints; 3.5 Use of Gene Expression Data in Metabolic Models 3.6 Use of Metabolomics Data in Metabolic Models: TMFA Example3.7 Integration of Multiple Omics Data Sets; 3.8 Future Directions and Applications to Strain Engineering; References; 4: Strain Improvement via Evolutionary Engineering; 4.0 Introduction; 4.1 Methodologies for Evolutionary Engineering; 4.1.1 Adaptive Evolution; 4.1.2 Genome Shuffling; 4.1.3 Global Transcriptional Machinery Engineering; 4.1.4 Transposon Insertion Mutagenesis; 4.1.5 Multiplex Automated Genome Engineering; 4.1.6 Tractable Multiplex Recombineering; 4.1.7 Chemically Induced Chromosomal Evolution 4.1.8 Multiscale Analysis of Library Enrichment (SCALE)4.1.9 Screening and Selection; 4.2 Examples of Evolutionary Engineering; 4.2.1 Enhancement of Product Yield and Productivity; 4.2.2 Extension of Substrate Range; 4.2.3 Improvement of Cellular Properties; 4.3 Conclusions and Future Prospects; Acknowledgments; References; 5: Rapid Fermentation Process Development and Optimization; 5.0 Introduction; 5.1 Overview of Classical Fermentation Process Development Methodology; 5.1.1 Noninvasive Sensor Technologies; 5.2 Fermentation Process Development and Optimization 5.2.1 Medium Design and Optimization5.2.2 Optimization of Growth Conditions; 5.3 Rapid Process Development and Optimization Using Conventional Fermentation System; 5.3.1 Dynamic DO Control to Determine Optimal Feed Rate for Carbon Source-Limited Fermentation; 5.3.2 Feed Forward Control for Carbon Source Excess Fermentation; 5.4 Strain Evaluation and Process Optimization under Scale-Down Conditions; 5.4.1 Identify Scale-Down Parameters; 5.4.2 Scale-Down of Mixing Related Parameters; 5.4.3 Oxygen Uptake Rate (OUR) Clipping; 5.4.4 Dissolved CO2 5.5 Control and Sensor Technologies for Minibioreactor |
| Record Nr. | UNINA-9910141378503321 |
| Hoboken, N.J., : Wiley, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Engineering complex phenotypes in industrial strains / / edited by Ranjan Patnaik
| Engineering complex phenotypes in industrial strains / / edited by Ranjan Patnaik |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley, 2012 |
| Descrizione fisica | 1 online resource (290 p.) |
| Disciplina | 579/.163 |
| Altri autori (Persone) | PatnaikRanjan <1969-> |
| Soggetto topico |
Genetic engineering
Industrial microorganisms |
| ISBN |
9781118433041
1118433041 9781118433034 1118433033 9781283645270 1283645270 9781118433003 1118433009 |
| Classificazione | TEC009010 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Title page; Copyright page; Contents; Foreword; Preface; Contributors; 1: Classical Strain Improvement; 1.0 Introduction; 1.1 The Approach Defined; 1.2 Mutagenesis; 1.2.1 Numerical Considerations in Screen Design; 1.2.2 Random Genetic Drift; 1.2.3 Forced Mutagenesis; 1.2.4 Strain Mating; 1.3 Genotypic Landscapes; 1.4 Screening; 1.4.1 Rational Screens; 1.4.2 Random Screens; 1.4.3 Screening Platforms; 1.5 Conclusions; References; 2: Tracer-Based Analysis of Metabolic Flux Networks; 2.0 Introduction; 2.1 Setting Up a Stoichiometric Network Model; 2.2 Small-Scale Models versus Genome Scale Models
2.3 Network Analysis: Maximum Theoretical Yield2.4 (Stoichiometric) Metabolic Flux Analysis; 2.5 Carrying Out a Labeling Experiment; 2.6 MEASURING ISOTOPE LABELING PATTERNS; 2.7 Tracer-Based MFA; 2.8 Validating Metabolic Flux Networks; 2.9 Conclusions; Acknowledgments; References; 3: Integration of "Omics" Data with Genome-Scale Metabolic Models; 3.0 Introduction; 3.1 Genome-Scale Metabolic Networks; 3.2 Constraint-Based Modeling Theory; 3.3 Current Analysis of Omics Data; 3.4 New Approaches to Developing Model Constraints; 3.5 Use of Gene Expression Data in Metabolic Models 3.6 Use of Metabolomics Data in Metabolic Models: TMFA Example3.7 Integration of Multiple Omics Data Sets; 3.8 Future Directions and Applications to Strain Engineering; References; 4: Strain Improvement via Evolutionary Engineering; 4.0 Introduction; 4.1 Methodologies for Evolutionary Engineering; 4.1.1 Adaptive Evolution; 4.1.2 Genome Shuffling; 4.1.3 Global Transcriptional Machinery Engineering; 4.1.4 Transposon Insertion Mutagenesis; 4.1.5 Multiplex Automated Genome Engineering; 4.1.6 Tractable Multiplex Recombineering; 4.1.7 Chemically Induced Chromosomal Evolution 4.1.8 Multiscale Analysis of Library Enrichment (SCALE)4.1.9 Screening and Selection; 4.2 Examples of Evolutionary Engineering; 4.2.1 Enhancement of Product Yield and Productivity; 4.2.2 Extension of Substrate Range; 4.2.3 Improvement of Cellular Properties; 4.3 Conclusions and Future Prospects; Acknowledgments; References; 5: Rapid Fermentation Process Development and Optimization; 5.0 Introduction; 5.1 Overview of Classical Fermentation Process Development Methodology; 5.1.1 Noninvasive Sensor Technologies; 5.2 Fermentation Process Development and Optimization 5.2.1 Medium Design and Optimization5.2.2 Optimization of Growth Conditions; 5.3 Rapid Process Development and Optimization Using Conventional Fermentation System; 5.3.1 Dynamic DO Control to Determine Optimal Feed Rate for Carbon Source-Limited Fermentation; 5.3.2 Feed Forward Control for Carbon Source Excess Fermentation; 5.4 Strain Evaluation and Process Optimization under Scale-Down Conditions; 5.4.1 Identify Scale-Down Parameters; 5.4.2 Scale-Down of Mixing Related Parameters; 5.4.3 Oxygen Uptake Rate (OUR) Clipping; 5.4.4 Dissolved CO2 5.5 Control and Sensor Technologies for Minibioreactor |
| Record Nr. | UNINA-9910816538703321 |
| Hoboken, N.J., : Wiley, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||