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Köp båda 2 för 2437 krJens Nielsen has a PhD degree (1989) in Biochemical Engineering from the Danish Technical University (DTU), and after that established his independent research group and was appointed full Professor there in 1998. He was Fulbright visiting professor at MIT in 1995-1996. At DTU he founded and directed the Center for Microbial Biotechnology. In 2008 he was recruited as Professor and Director to Chalmers University of Technology, Sweden. Jens Nielsen has received numerous Danish and international awards including the Nature Mentor Award, and is member of several academies, including the National Academy of Engineering in USA and the Royal Swedish Academy of Science. He is a founding president of the International Metabolic Engineering Society. Stefan Hohmann is Head of the Department of Biology and Biological Engineering at Chalmers University (Sweden). He studied biology and microbiology at the Technische Universitt Darmstadt (Germany), where he received his PhD in 1987 and became professor in 1993. He held positions as visiting professor at the Katholieke Universiteit Leuven (Belgium) and the University of the Orange Free State (South Africa), before joining the University of Gothenburg in 1999 as professor, a position he hold until his change to Chalmers University in 2015. Stefan Hohmann serves as chairman of several committees and is the Swedish representative at the European Molecular Biology Laboratory (EMBL) Research Council. Sang Yup Lee is Distinguished Professor at the Department of Chemical and Biomolecular Engineering at the Korea Advanced Institute of Science and Technology (KAIST). He is currently the Director of the Center for Systems and Synthetic Biotechnology, Director of the BioProcess Engineering Research Center, and Director of the Bioinformatics Research Center. He received numerous awards, including the National Order of Merit, the Merck Metabolic Engineering Award and the Elmer Gaden Award. Lee is the Editor-in-Chief of the Biotechnology Journal and Associate Editor and board member of numerous other journals. Lee is currently serving as a member of Presidential Advisory Committee on Science and Technology (Korea). Professor Gregory Stephanopoulos is the W. H. Dow Professor of Chemical Engineering at the Massachusetts Institute of Technology (MIT, USA) and Director of the MIT Metabolic Engineering Laboratory. He is also Instructor of Bioengineering at Harvard Medical School (since 1997). He has been recognized by numerous awards from the American Institute of Chemical Engineers (AIChE) (Wilhelm, Walker and Founders awards), American Chemical Society (ACS), Society of industrial Microbiology (SIM), BIO (Washington Carver Award), the John Fritz Medal of the American Association of Engineering Societies, and others. In 2003 he was elected member of the National Academy of Engineering (USA) and in 2014 President of AIChE.
List of Contributors XV About the Series Editors XXIII 1 Integrative Analysis of Omics Data 1 Tobias sterlund, Marija Cvijovic, and Erik Kristiansson Summary 1 1.1 Introduction 1 1.2 Omics Data and Their Measurement Platforms 4 1.2.1 Omics Data Types 4 1.2.2 Measurement Platforms 5 1.3 Data Processing: Quality Assessment, Quantification, Normalization, and Statistical Analysis 6 1.3.1 Quality Assessment 7 1.3.2 Quantification 9 1.3.3 Normalization 10 1.3.4 Statistical Analysis 11 1.4 Data Integration: From a List of Genes to Biological Meaning 12 1.4.1 Data Resources for Constructing Gene Sets 13 1.4.2 Gene Set Analysis 14 1.4.3 Networks and Network Topology 17 1.5 Outlook and Perspectives 18 References 19 2 13C Flux Analysis in Biotechnology and Medicine 25 Yi Ern Cheah, Clinton M. Hasenour, and Jamey D. Young 2.1 Introduction 25 2.1.1 Why Study Metabolic Fluxes? 25 2.1.2 Why are Isotope Tracers Important for Flux Analysis? 26 2.1.3 How are Fluxes Determined? 28 2.2 Theoretical Foundations of 13C MFA 29 2.2.1 Elementary Metabolite Units (EMUs) 30 2.2.2 Flux Uncertainty Analysis 31 2.2.3 Optimal Design of Isotope Labeling Experiments 32 2.2.4 Isotopically Nonstationary MFA (INST-MFA) 34 2.3 Metabolic Flux Analysis in Biotechnology 36 2.3.1 13C MFA for Host Characterization 36 2.3.2 13C MFA for Pinpointing Yield Losses and Futile Cycles 39 2.3.3 13C MFA for Bottleneck Identification 41 2.4 Metabolic Flux Analysis in Medicine 42 2.4.1 Liver Glucose and Oxidative Metabolism 43 2.4.2 Cancer Cell Metabolism 47 2.4.3 Fuel Oxidation and Anaplerosis in the Heart 48 2.4.4 Metabolism in Other Tissues: Pancreas, Brain, Muscle, Adipose, and Immune Cells 49 2.5 Emerging Challenges for 13C MFA 50 2.5.1 Theoretical and Computational Advances: Multiple Tracers, Co-culture MFA, Dynamic MFA 50 2.5.2 Genome-Scale 13C MFA 51 2.5.3 New Measurement Strategies 52 2.5.4 High-Throughput MFA 53 2.5.5 Application of MFA to Industrial Bioprocesses 53 2.5.6 Integrating MFA with Omics Measurements 54 2.6 Conclusion 55 Acknowledgments 55 Disclosure 55 References 55 3 Metabolic Modeling for Design of Cell Factories 71 Mingyuan Tian, Prashant Kumar, Sanjan T. P. Gupta, and Jennifer L. Reed Summary 71 3.1 Introduction 71 3.2 Building and Refining Genome-Scale Metabolic Models 72 3.2.1 Generate a Draft Metabolic Network (Step 1) 74 3.2.2 Manually Curate the Draft Metabolic Network (Step 2) 75 3.2.3 Develop a Constraint-Based Model (Step 3) 77 3.2.4 Revise the Metabolic Model through Reconciliation with Experimental Data (Step 4) 79 3.2.5 Predicting the Effects of Genetic Manipulations 81 3.3 Strain Design Algorithms 83 3.3.1 Fundamentals of Bilevel Optimization 84 3.3.2 Algorithms Involving Only Gene/Reaction Deletions 94 3.3.3 Algorithms Involving Gene Additions 94 3.3.4 Algorithms Involving Gene Over/Underexpression 95 3.3.5 Algorithms Involving Cofactor Changes 98 3.3.6 Algorithms Involving Multiple Design Criteria 99 3.4 Case Studies 100 3.4.1 Strains Producing Lactate 100 3.4.2 Strains Co-utilizing Sugars 100 3.4.3 Strains Producing 1,4-Butanediol 102 3.5 Conclusions 103 Acknowledgments 103 References 104 4 Genome-Scale Metabolic Modeling and In silico Strain Design of Escherichia coli 109 Meiyappan Lakshmanan, Na-Rae Lee, and Dong-Yup Lee 4.1 Introduction 109 4.2 The COBRA Approach 110 4.3 History of E. coli Metabolic Modeling 111 4.3.1 Pre-genomic-era Models 111 4.3.2 Genome-Scale Models 112 4.4 In silico Model-Based Strain Design of E. coli Cell Factories 115 4.4.1 Gene Deletions 127 4.4.2 Gene Up/Downregulations 127 4.4.3 Gene Insertions 128 4.4.4 Cofactor Engineering 128 4.4.5 Other Approaches 128 4.5 Future Directions of Model-Guided Strain Design in E. coli 129 References 130 5 Accelerating the Drug Development Pipeline with Genome-Scale Metabolic Network Reconstructions 139 Bon