Computational systems biology is the term that we use to describe computational methods to identify, infer, model, and store relationships between the molecules, pathways, and cells (''systems'') involved in a living organism. Based on this definition, the field of computational systems biology has been in existence for some time. However, the recent confluence of high-throughput methodology for biological data gathering, genome-scalesequencing, andcomputationalprocessingpowerhasdrivena reinvention and expansion of this field. The expansions include not only modeling of small metabolic (1-3) and signaling systems (2, 4) but also modeling of the relati- ships between biological components in very large systems, including whole cells and organisms (5-15). Generally, these models provide a general overview of one or more aspects of these systems and leave the determination of details to experimentalists focused on smaller subsystems. The promise of such approaches is that they will elucidate patterns, relationships, and general features, which are not evident from examining specific components or subsystems. These predictions are either interesting in and of themselves (e. g., the identification of an evolutionary pattern) or interesting andvaluabletoresearchersworkingonaparticularproblem(e. g., highlightapreviously unknown functional pathway). Two events have occurred to bring the field of computational systems biology to theforefront. Oneistheadventofhigh-throughputmethodsthathavegeneratedlarge amounts of information about particular systems in the form of genetic studies, gene and protein expression analyses and metabolomics. With such tools, research to c- sidersystemsasawholearebeingconceived, planned, andimplementedexperimentally on an ever more frequent andwider scale.
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a broad range of topics related to computational systems biology, including mechanistic modeling, high-throughput data analysis, biological network analysis and data representation and managementProvides a number of clearly described, det. N° de réf. du vendeur 447956619
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computational systems biology is the term that we use to describe computational methods to identify, infer, model, and store relationships between the molecules, pathways, and cells (''systems'') involved in a living organism. Based on this definition, the field of computational systems biology has been in existence for some time. However, the recent confluence of high-throughput methodology for biological data gathering,genome-scalesequencing,andcomputationalprocessingpowerhasdrivena reinvention and expansion of this field. The expansions include not only modeling of small metabolic (1-3) and signaling systems (2, 4) but also modeling of the relati- ships between biological components in very large systems, including whole cells and organisms (5-15). Generally, these models provide a general overview of one or more aspects of these systems and leave the determination of details to experimentalists focused on smaller subsystems. The promise of such approaches is that they will elucidate patterns, relationships, and general features, which are not evident from examining specific components or subsystems. These predictions are either interesting in and of themselves (e. g. , the identification of an evolutionary pattern) or interesting andvaluabletoresearchersworkingonaparticularproblem(e. g. ,highlightapreviously unknown functional pathway). Two events have occurred to bring the field of computational systems biology to theforefront. Oneistheadventofhigh-throughputmethodsthathavegeneratedlarge amounts of information about particular systems in the form of genetic studies, gene and protein expression analyses and metabolomics. With such tools, research to c- sidersystemsasawholearebeingconceived,planned,andimplementedexperimentally on an ever more frequent and wider scale. 612 pp. Englisch. N° de réf. du vendeur 9781493956449
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Taschenbuch. Etat : Neu. Neuware -Computational systems biology is the term that we use to describe computational methods to identify, infer, model, and store relationships between the molecules, pathways, and cells (¿¿systems¿¿) involved in a living organism. Based on this definition, the field of computational systems biology has been in existence for some time. However, the recent confluence of high-throughput methodology for biological data gathering,genome-scalesequencing,andcomputationalprocessingpowerhasdrivena reinvention and expansion of this field. The expansions include not only modeling of small metabolic (1¿3) and signaling systems (2, 4) but also modeling of the relati- ships between biological components in very large systems, including whole cells and organisms (5¿15). Generally, these models provide a general overview of one or more aspects of these systems and leave the determination of details to experimentalists focused on smaller subsystems. The promise of such approaches is that they will elucidate patterns, relationships, and general features, which are not evident from examining specific components or subsystems. These predictions are either interesting in and of themselves (e. g. , the identification of an evolutionary pattern) or interesting andvaluabletoresearchersworkingonaparticularproblem(e. g. ,highlightapreviously unknown functional pathway). Two events have occurred to bring the field of computational systems biology to theforefront. Oneistheadventofhigh-throughputmethodsthathavegeneratedlarge amounts of information about particular systems in the form of genetic studies, gene and protein expression analyses and metabolomics. With such tools, research to c- sidersystemsasawholearebeingconceived,planned,andimplementedexperimentally on an ever more frequent andwider scale.Humana Press in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 612 pp. Englisch. N° de réf. du vendeur 9781493956449
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Computational systems biology is the term that we use to describe computational methods to identify, infer, model, and store relationships between the molecules, pathways, and cells (''systems'') involved in a living organism. Based on this definition, the field of computational systems biology has been in existence for some time. However, the recent confluence of high-throughput methodology for biological data gathering,genome-scalesequencing,andcomputationalprocessingpo werhasdrivena reinvention and expansion of this field. The expansions include not only modeling of small metabolic (1-3) and signaling systems (2, 4) but also modeling of the relati- ships between biological components in very large systems, including whole cells and organisms (5-15). Generally, these models provide a general overview of one or more aspects of these systems and leave the determination of details to experimentalists focused on smaller subsystems. The promise of such approaches is that they will elucidate patterns, relationships, and general features, which are not evident from examining specific components or subsystems. These predictions are either interesting in and of themselves (e. g. , the identification of an evolutionary pattern) or interesting andvaluabletoresearchersworkingonaparticularproblem(e. g. ,highlightapreviously unknown functional pathway). Two events have occurred to bring the field of computational systems biology to theforefront. Oneistheadventofhigh-throughputmethodsthathavegeneratedlarge amounts of information about particular systems in the form of genetic studies, gene and protein expression analyses and metabolomics. With such tools, research to c- sidersystemsasawholearebeingconceived,planned,andimplementedexperimentally on an ever more frequent andwider scale. N° de réf. du vendeur 9781493956449
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