LEADER 00911nam0-22003131i-450- 001 990006719130403321 005 20001010 035 $a000671913 035 $aFED01000671913 035 $a(Aleph)000671913FED01 035 $a000671913 100 $a20001010d--------km-y0itay50------ba 101 0 $aita 105 $ay-------001yy 200 1 $aSensitivity analysis in linear regression$fSamprit Chatterjee, Ali S. Hadi.- 210 $aNew York$cJ. Wiley & Sons$d1988 215 $aXVI+315 p.,23 cm 225 1 $aWiley series in probability and mathematical statistics$v 676 $a519.5 700 1$aChatterjee,$bSamprit$014454 702 1$aHadi,$bAli S. 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990006719130403321 952 $aVI E 307$b6748$fFSPBC 959 $aFSPBC 996 $aSensitivity analysis in linear regression$9126064 997 $aUNINA DB $aGEN01 LEADER 01057nam--2200373---450- 001 990003623810203316 005 20120215103423.0 010 $a978-88-604-2910-0 035 $a000362381 035 $aUSA01000362381 035 $a(ALEPH)000362381USA01 035 $a000362381 100 $a20120215d2011----km-y0itay50------ba 101 0 $aita 102 $aIT 105 $a||||||||001yy 200 1 $aNapoli, eppur si muove$fPasquale Belfiore 210 $aNapoli$cGuida$d2011 215 $a290 p.$d23 cm 225 2 $aOrizzonti 410 0$12001$aOrizzonti 606 0 $aArchitettura$xNapoli$z2000-2009 606 0 $aUrbanistica$yNapoli$z2000-2009$2BNCF 676 $a711.40945731 700 1$aBELFIORE,$bPasquale$08668 801 0$aIT$bsalbc$gISBD 912 $a990003623810203316 951 $aXII.3.B. 250$b234613 L.M.$cXII.3.B.$d00306675 959 $aBK 969 $aUMA 979 $aPASSARO$b90$c20120215$lUSA01$h1031 979 $aPASSARO$b90$c20120215$lUSA01$h1034 996 $aNapoli, eppur si muove$91136988 997 $aUNISA LEADER 01244nam0-22003851i-450- 001 990005473520203316 005 20060313120000.0 035 $a000547352 035 $aUSA01000547352 035 $a(ALEPH)000547352USA01 035 $a000547352 100 $a20010829d1980-------|0enac50------ba 101 $aeng 102 $aUS 105 $a|||| ||||| 200 1 $aApproximation Theorems of Mathematical Statistics$fRobert J. Serfling - New York : John Wiley & sons, 1980 210 $d367 p. : graf. ; 23 cm. 225 2$aWiley series in probability and statistics 410 1$12001$aWiley series in probability and statistics 606 $aStatistiche matematiche$2FI 620 $dNew York 676 $a519.5$cStatistica matematica$v21 700 1$aSERFLING,$bRobert J.$088863 712 $aJohn Wiley & Sons, Inc 801 $aIT$bSOL$c20120104 912 $a990005473520203316 950 $aDIP.TO SCIENZE ECONOMICHE - (SA)$dDS 500 519.5 SER$eST11664 DISES 951 $a500 519.5 SER$b1664 DISES 959 $aBK 969 $aDISES 979 $c20121027$lUSA01$h1532 979 $c20121027$lUSA01$h1613 996 $aApproximation theorems of mathematical statistics$9194947 997 $aUNISA NUM $aUSA7632 LEADER 01885nam 2200421 a 450 001 9910701078803321 005 20120416151618.0 035 $a(CKB)5470000002414247 035 $a(OCoLC)785831608 035 $a(EXLCZ)995470000002414247 100 $a20120416d2004 ua 0 101 0 $aeng 135 $aurmn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEvaluation of labor exchange services in a one-stop delivery system environment$b[electronic resource] $efinal report /$fLouis Jacobson ... [and others] ; prepared for U.S. Department of Labor ; prepared by WESTAT 210 1$aWashington, DC :$cU.S. Dept. of Labor, Employment and Training Administration,$d[2004] 215 $a1 online resource (262 unnumbered pages) 225 1 $aEmployment and Training Administration occasional paper ;$v2004-09 300 $aTitle from title screen (viewed on Apr. 16, 2012). 300 $a"February 2004." 300 $a"This report has been funded, either wholly or in part, with Federal funds from the U.S. Department of Labor, Employment and Training Administration under Contract Number X-6879-8-00-80-30." 320 $aIncludes bibliographical references (page [182-184]). 517 $aEvaluation of labor exchange services in a one-stop delivery system environment 606 $aEmployment agencies$zUnited States 606 $aUnemployed$xServices for$zUnited States 615 0$aEmployment agencies 615 0$aUnemployed$xServices for 700 $aJacobson$b Louis$01406703 712 02$aUnited States.$bEmployment and Training Administration. 712 02$aWestat, Inc. 801 0$bGPO 801 1$bGPO 906 $aBOOK 912 $a9910701078803321 996 $aEvaluation of labor exchange services in a one-stop delivery system environment$93534782 997 $aUNINA LEADER 10916nam 2200553 450 001 9910829921803321 005 20230630003411.0 010 $a3-527-82345-X 010 $a3-527-82344-1 010 $a3-527-82346-8 035 $a(CKB)4100000011953300 035 $a(MiAaPQ)EBC6637758 035 $a(Au-PeEL)EBL6637758 035 $a(OCoLC)1257260667 035 $a(EXLCZ)994100000011953300 100 $a20220201d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aMetabolic engineering $econcepts and applications /$fedited by Sang Yup Lee, Jens Nielsen, Gregory Stephanopoulos 210 1$aWeinheim, Germany :$cWILEY-VCH,$d[2021] 210 4$dİ2021 215 $a1 online resource (962 pages) 225 1 $aAdvanced Biotechnology ;$vVolume 13b 311 $a3-527-34662-7 327 $aCover -- Title Page -- Copyright -- Contents -- Preface -- Part 1 Concepts -- Chapter 1 Metabolic Engineering Perspectives -- 1.1 History and Overview of Metabolic Engineering -- 1.2 Understanding Cellular Metabolism and Physiology -- 1.2.1 Computational Methods in Understanding Metabolism -- 1.2.2 Experimental Methods in Understanding Metabolism -- 1.3 General Approaches to Metabolic Engineering -- 1.3.1 Rational Metabolic Engineering -- 1.3.2 Combinatorial Metabolic Engineering -- 1.3.3 Systems Metabolic Engineering -- 1.4 Host Organism Selection -- 1.5 Substrate Considerations -- 1.6 Metabolic Engineering and Synthetic Biology -- 1.7 The Future of Metabolic Engineering -- References -- Chapter 2 Genome?Scale Models: Two Decades of Progress and a 2020 Vision -- 2.1 Introduction -- 2.2 Flux Balance Analysis -- 2.2.1 Dynamic Mass Balances -- 2.2.2 Analogy to Deriving Enzymatic Rate Equations -- 2.2.3 Formulating Flux Balances at the Genome?Scale -- 2.2.4 Constrained Optimization -- 2.2.5 Principles -- 2.2.6 Additional Constraints -- 2.2.7 Flux-Concentration Duality -- 2.2.8 Recap -- 2.3 Network Reconstruction -- 2.3.1 Assembling the Reactome -- 2.3.2 Basic Principles of Network Reconstruction -- 2.3.3 Curation -- 2.3.4 GEMs Have a Genomic Basis -- 2.3.5 Computational Queries -- 2.3.6 Scope Expansion -- 2.3.7 Knowledge Bases -- 2.3.8 Availability of GEMs -- 2.3.9 Recap -- 2.4 Brief History of the GEM for E. coli -- 2.4.1 Origin -- 2.4.2 Model Organism -- 2.4.3 Key Predictions -- 2.4.4 Design Algorithms -- 2.4.5 Scope Expansions -- 2.4.6 Recap -- 2.5 From Metabolism to the Proteome -- 2.5.1 ME Models -- 2.5.2 Capabilities of ME Models -- 2.5.2.1 Growth?Coupled Metabolic Designs Can Be Reproduced in GEMs -- 2.5.2.2 ME Models Can Reflect Properties of the Metalloproteome -- 2.5.2.3 ME Models Can Compute the Biomass Objective Function. 327 $a2.5.2.4 Computing Stresses -- 2.5.3 Recapitulation -- 2.6 Current Developments -- 2.6.1 Kinetics -- 2.6.2 Transcriptional Regulation -- 2.6.2.1 iModulons -- 2.6.2.2 Activities -- 2.6.3 Protein Structures -- 2.7 Broader Perspectives -- 2.7.1 Distal Causation -- 2.7.2 Contextualization of GEMs Within Workflows -- 2.8 What Does the Future Look Like for GEMs? -- Disclaimer -- Acknowledgments -- References -- Chapter 3 Quantitative Metabolic Flux Analysis Based on Isotope Labeling -- 3.1 Introduction -- 3.1.1 What Metabolic Flux Analysis Is About -- 3.1.2 The Variants of 13C?MFA -- 3.2 A Toy Example Illustrates the Basic Principles -- 3.2.1 Fluxomics: More Than Just a Branch of Metabolomics -- 3.2.2 Isotope Labeling: The Key to Metabolic Fluxes -- 3.2.3 From the Data to the Intracellular Fluxes -- 3.2.4 INST?13C?MFA: Metabolic Stationary, but Isotopically Nonstationary -- 3.2.5 From Measurements to Flux Estimates: Parameter Fitting -- 3.2.6 Flux Estimates Have Confidence Bounds: Statistical Analysis -- 3.2.7 The Classical Approach at Metabolic and Isotopic Stationary State -- 3.2.8 An Additional Source of Information: Carbon Atom Transitions -- 3.2.9 Input Labeling Design: How Informative Can an Experiment Be Made? -- 3.2.10 The Isotopomers of a Single Metabolite can be a Rich Source of Information -- 3.2.11 Bidirectional Reaction Steps: More Than Just Nuisance Factors -- 3.2.12 Isotopomer Fractions Cannot Be Measured Comprehensively -- 3.3 Lessons Learned from the Example -- 3.3.1 Definition of 13C?MFA Revisited -- 3.3.2 Statistical Evaluation and Optimal Experimental Design -- 3.4 How to Configure an Isotope Labeling Experiment -- 3.4.1 Modeling and Simulation of Isotope Labeling Experiments -- 3.4.2 Metabolic Network Specification -- 3.4.3 Atom Transition Network Specification -- 3.4.4 Input Labeling Composition -- 3.4.5 Measurement Specification. 327 $a3.4.6 Flux Constraints -- 3.4.7 In Silico Experimental ILE Design -- 3.5 Putting Theory into Practice -- 3.5.1 A Recipe How to Start -- 3.5.2 Metabolic and Isotopic Stationarity -- 3.5.3 Measuring Extracellular Fluxes -- 3.5.4 Administering Labeled Substrate(s) -- 3.5.5 Metabolomics: Sampling, Sample Preparation, and Analytical Procedures -- 3.5.6 Adjusting Labeling Enrichments for Isotopic Steady State Approximation -- 3.5.7 Correcting Labeling Enrichments for Natural Isotope Abundance -- 3.5.8 Simulation of Labeling Data and Flux Estimation -- 3.5.9 Delicacies of INST?13C?MFA -- 3.6 Future Challenges of 13C?MFA -- Acknowledgments -- Abbreviations -- References -- Chapter 4 Proteome Constraints in Genome?Scale Models -- 4.1 Introduction -- 4.2 Cellular Constraints -- 4.3 Formulation of Proteome Constraints -- 4.3.1 Coarse?Grained Integration of Proteome Constraints -- 4.3.2 Fine?Tuned Integration of Proteome Constraints -- 4.4 Perspectives -- References -- Chapter 5 Kinetic Models of Metabolism -- 5.1 Introduction -- 5.2 Definition of Enzyme Kinetics -- 5.2.1 Michaelis-Menten Formula -- 5.3 Factors Affecting Intracellular Enzyme Kinetics -- 5.4 Kinetic Model: Definition and Scope -- 5.4.1 What Is a Kinetic Model? -- 5.4.2 Scope of Kinetic Models -- 5.4.3 How to Build a Functional Kinetic Model? -- 5.5 Main Mathematical Expressions in Description of Reaction Rates -- 5.5.1 Mechanistic Rate Expressions -- 5.6 Approximative Rate Expressions -- 5.7 Approaches to Assign Parameters in the Rate Expressions -- 5.7.1 Direct Measurements of Kinetic Parameters in Enzyme Assays -- 5.7.2 Querying Databases -- 5.7.3 Inferring from Measured Fluxes -- 5.7.4 Parameters Inference Using the Statistical Analysis -- 5.8 Applications -- 5.9 Perspectives -- References -- Chapter 6 Metabolic Control Analysis. 327 $a6.1 The Metabolic Engineering Context of Metabolic Control Analysis -- 6.2 MCA Theory -- 6.2.1 Metabolic Steady State -- 6.2.2 Flux Control Coefficients -- 6.2.3 Examples of the Flux-Enzyme Relationship -- 6.2.4 Flux Summation Theorem -- 6.2.5 Concentration Control Coefficients -- 6.2.6 Linking Control Coefficients to Enzyme Properties -- 6.2.6.1 Enzyme Rate Equations and Elasticity Coefficients -- 6.2.6.2 Elasticities and Control Coefficients -- 6.2.6.3 Block Coefficients and Top?Down Analysis -- 6.2.7 Feedback Inhibition -- 6.2.8 Large Alterations of Enzyme Activity -- 6.3 Implications of MCA for Metabolic Engineering Strategies -- 6.3.1 Abolishing Feedback Inhibition -- 6.3.2 Increasing Demand for Product -- 6.3.3 Inhibition of Competing Pathways -- 6.3.4 Designing Large Changes in Metabolic Flux -- 6.3.4.1 Yeast Tryptophan Synthesis -- 6.3.4.2 The Universal Method -- 6.3.4.3 Bacterial Production of Aromatic Amino Acids -- 6.3.4.4 Penicillin and Other Instances -- 6.3.5 Impacts on Yield from a Growing System -- 6.4 Conclusion -- Appendix 6.A: Feedback Inhibition Simulation -- References -- Chapter 7 Thermodynamics of Metabolic Pathways -- 7.1 Bioenergetics in Life and in Metabolic Engineering -- 7.2 Thermodynamics?Based Flux Analysis Workflow -- 7.2.1 Thermodynamic Model Curation -- 7.2.1.1 Estimation of the Standard Free Energies of Formation -- 7.2.1.2 Compensating for Compartment?Specific Ionic Strength and pH -- 7.2.1.3 Compensating the Free Energy of Formation for Isomer Distributions -- 7.2.1.4 Computing the Transformed Free Energies of Reaction -- 7.2.2 Mathematical Formulation -- 7.3 Thermodynamics?Based Flux Analysis Applications -- 7.3.1 Constraining the Flux Space with Metabolomics Data -- 7.3.2 Characterizing the Feasible Concentration Space -- 7.4 Conclusion and Future Perspectives -- References -- Chapter 8 Pathway Design. 327 $aDefinition -- 8.1 De Novo Design of Metabolic Pathways -- 8.1.1 Manual Versus Computational Design -- 8.2 Pathway Design Workflow -- 8.2.1 Biochemical Search Space -- 8.2.1.1 Reaction Prediction -- 8.2.1.2 Retrobiosynthesis -- 8.2.1.3 Network Data Representation -- 8.2.2 Pathway Search -- 8.2.2.1 Stoichiometric Matrix?Based Search -- 8.2.2.2 Graph?Based Search -- 8.2.2.3 Pathway Ranking -- 8.2.3 Enzyme Assignment -- 8.2.3.1 Enzyme Prediction for Orphan and Novel Reactions -- 8.2.3.2 Choice of Protein Sequence -- 8.2.4 Pathway Feasibility -- 8.2.4.1 Chassis Metabolic Model -- 8.2.4.2 Stoichiometric Feasibility -- 8.2.4.3 Thermodynamic Feasibility -- 8.2.4.4 Kinetic Feasibility -- 8.2.4.5 Toxicity of Intermediates -- 8.3 Applications -- 8.3.1 Available Tools for Pathway Design -- 8.3.2 Successful Applications of Pathway Design Tools -- 8.3.3 Practical Example of Pathway Design -- 8.3.3.1 Creating a Biochemical Network Around BDO -- 8.3.3.2 Search for Biosynthetic Pathways -- 8.3.3.3 Finding Enzymes for Novel Reactions -- 8.3.3.4 Stoichiometric and Thermodynamic Pathway Evaluation -- 8.3.3.5 Overall Ranking of Pathways -- 8.4 Conclusions and Future Perspectives -- References -- Chapter 9 Metabolomics -- 9.1 Introduction -- 9.2 Fundamentals -- 9.2.1 Experimental Design -- 9.2.2 Targeted and Untargeted Metabolomics -- 9.2.3 Sequences and Standards -- 9.3 Analytical Techniques -- 9.3.1 Sample Preparation -- 9.3.2 Separation Techniques -- 9.3.2.1 Liquid Chromatography -- 9.3.2.2 Gas Chromatography -- 9.3.2.3 Alternative Separation Techniques -- 9.3.3 Mass Spectrometry -- 9.3.3.1 Ionization Techniques -- 9.3.3.2 Low?Resolution MS -- 9.3.3.3 High?Resolution MS -- 9.3.3.4 Acquisition Modes for Targeted MS -- 9.3.3.5 Acquisition Modes for Untargeted Metabolomics -- 9.4 Data Analysis -- 9.4.1 Data Processing in Untargeted Metabolomics. 327 $a9.4.1.1 Preprocessing of Individual MS Runs. 410 0$aAdvanced biotechnology ;$vVolume 13b. 606 $aMicrobial biotechnology 606 $aMicrobial genetic engineering 615 0$aMicrobial biotechnology. 615 0$aMicrobial genetic engineering. 676 $a660.62 702 $aYi$b Sang-yo?p$f1964- 702 $aNielsen$b Jens 702 $aStephanopoulos$b Gregory 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910829921803321 996 $aMetabolic engineering$92425022 997 $aUNINA