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This thesis uses a systems-level approach to study the cellular metabolism, unveiling new mechanisms and responses that were impossible to reach with traditional reductionists procedures. The results reported here have a potential application in areas like metabolic engineering and disease treatment. They could also be used in determining the accuracy of the gene essentiality of new genome-scale reconstructions. Different methods and techniques, within the contexts of Systems Biology and the field known as Complex Networks Analysis have been applied in this work to show different features of the robustness of metabolic networks. The specific issues addressed here range from pure topological aspec ts of the networks themselves to the balance of biochemical fluxes.
Big data, genomics, and quantitative approaches to network-based analysis are combining to advance the frontiers of medicine as never before. Network Medicine introduces this rapidly evolving field of medical research, which promises to revolutionize the diagnosis and treatment of human diseases. With contributions from leading experts that highlight the necessity of a team-based approach in network medicine, this definitive volume provides readers with a state-of-the-art synthesis of the progress being made and the challenges that remain. Medical researchers have long sought to identify single molecular defects that cause diseases, with the goal of developing silver-bullet therapies to treat them. But this paradigm overlooks the inherent complexity of human diseases and has often led to treatments that are inadequate or fraught with adverse side effects. Rather than trying to force disease pathogenesis into a reductionist model, network medicine embraces the complexity of multiple influences on disease and relies on many different types of networks: from the cellular-molecular level of protein-protein interactions to correlational studies of gene expression in biological samples. The authors offer a systematic approach to understanding complex diseases while explaining network medicine’s unique features, including the application of modern genomics technologies, biostatistics and bioinformatics, and dynamic systems analysis of complex molecular networks in an integrative context. By developing techniques and technologies that comprehensively assess genetic variation, cellular metabolism, and protein function, network medicine is opening up new vistas for uncovering causes and identifying cures of disease.
Systems Biology aims at deciphering the genotype-phenotype relationships at the levels of genes, transcripts (RNAs), peptides, proteins, metabolites, and environmental factors participating in complex cellular networks in order to reveal the mechanisms and principles governing the behavior of complex biological systems. Yeast Systems Biology: Methods and Protocols presents an up-to-date view of the optimal characteristics of the yeast Saccharomyces cerevisiae as a model eukaryote, perspective on the latest experimental and computational techniques for systems biology studies, most of which were first designed for and validated in yeast, and selected examples of yeast systems biology studies and their applications in biotechnology and medicine. These experiments under controlled conditions can uncover the complexity and interplay of biological networks with their dynamics, basic principles of internal organization, and balanced orchestrated functions between organelles in direct interaction with the environment as well as the characterization of short and long-term effects of perturbations and dysregulation of networks that may illuminate the origin of complex human diseases. Written for the highly successful Methods in Molecular BiologyTM series, this volume contains the kind of detailed description and implementation advice that is crucial for getting optimal results. Practical and cutting-edge, Yeast Systems Biology: Methods and Protocols serves researchers interested in comprehensive systems biology strategies in well-defined model systems with specific objectives as well as a better knowledge of the latest post-genomic strategies at all ‘omic levels and computational approaches towards analysis, integration, and modeling of biological systems, from single-celled organisms to higher eukaryotes.
Key introductory text for graduate students and researchers in physics, biology and biochemistry.
Many potential applications of synthetic and systems biology are relevant to the challenges associated with the detection, surveillance, and responses to emerging and re-emerging infectious diseases. On March 14 and 15, 2011, the Institute of Medicine's (IOM's) Forum on Microbial Threats convened a public workshop in Washington, DC, to explore the current state of the science of synthetic biology, including its dependency on systems biology; discussed the different approaches that scientists are taking to engineer, or reengineer, biological systems; and discussed how the tools and approaches of synthetic and systems biology were being applied to mitigate the risks associated with emerging infectious diseases. The Science and Applications of Synthetic and Systems Biology is organized into sections as a topic-by-topic distillation of the presentations and discussions that took place at the workshop. Its purpose is to present information from relevant experience, to delineate a range of pivotal issues and their respective challenges, and to offer differing perspectives on the topic as discussed and described by the workshop participants. This report also includes a collection of individually authored papers and commentary.
This comprehensively revised second edition of Computational Systems Biology discusses the experimental and theoretical foundations of the function of biological systems at the molecular, cellular or organismal level over temporal and spatial scales, as systems biology advances to provide clinical solutions to complex medical problems. In particular the work focuses on the engineering of biological systems and network modeling. - Logical information flow aids understanding of basic building blocks of life through disease phenotypes - Evolved principles gives insight into underlying organizational principles of biological organizations, and systems processes, governing functions such as adaptation or response patterns - Coverage of technical tools and systems helps researchers to understand and resolve specific systems biology problems using advanced computation - Multi-scale modeling on disparate scales aids researchers understanding of dependencies and constraints of spatio-temporal relationships fundamental to biological organization and function.
Genetic alterations in cancer, in addition to being the fundamental drivers of tumorigenesis, can give rise to a variety of metabolic adaptations that allow cancer cells to survive and proliferate in diverse tumor microenvironments. This metabolic flexibility is different from normal cellular metabolic processes and leads to heterogeneity in cancer metabolism within the same cancer type or even within the same tumor. In this book, we delve into the complexity and diversity of cancer metabolism, and highlight how understanding the heterogeneity of cancer metabolism is fundamental to the development of effective metabolism-based therapeutic strategies. Deciphering how cancer cells utilize various nutrient resources will enable clinicians and researchers to pair specific chemotherapeutic agents with patients who are most likely to respond with positive outcomes, allowing for more cost-effective and personalized cancer therapeutic strategies.
Functional Metabolism of Cells is the first comprehensive survey of metabolism, offering an in-depth examination of metabolism and regulation of carbohydrates, lipids, and amino acids. It provides a basic background on metabolic regulation and adaptation as well as the chemical logic of metabolism, and covers the interrelationship of metabolism to life processes of the whole organism. The book lays out a structured approach to the metabolic basis of disease, including discussion of the normal pathways of metabolism, altered pathways leading to disease, and use of molecular genetics in diagnosis and treatment of disease. It also takes a unique comparative approach in which human metabolism is a reference for metabolism in microorganisms and plant design, and presents novel coverage of development and aging, and human health and animal adaptation. The final chapter reviews the past and future promise of new genetic approaches to treatment and bioinformatics. This, the most exhaustive treatment of metabolism currently available, is a useful text for advanced undergraduates and graduates in biochemistry, cell/molecular biology, and biomedicine, as well as biochemistry instructors and investigators in related fields.
Metabolic and cellular engineering, as presented in this book, is a powerful alliance of two technologies: genetics-molecular biology and fermentation technology. Both are driven by continuous refinement of the basic understanding of metabolism, physiology and cellular biology (growth, division, differentiation), as well as the development of new mathematical modeling techniques. The authors' approach is original in that it integrates several disciplines into a coordinated scheme, i.e. microbial physiology and bioenergetics, thermodynamics and enzyme kinetics, biomathematics and biochemistry, genetics and molecular biology. Thus, it is called a transdisciplinary approach (TDA). The TDA provides the basis for the rational design of microorganisms or cells in a way that has rarely been utilized to its full extent.