Systems Biology: Properties of Reconstructed NetworksGenome sequences are now available that enable us to determine the biological components that make up a cell or an organism. The discipline of systems biology examines how these components interact and form networks, and how the networks generate whole cell functions corresponding to observable phenotypes. This textbook, devoted to systems biology, describes how to model networks, how to determine their properties, and how to relate these to phenotypic functions. The prerequisites are some knowledge of linear algebra and biochemistry. Though the links between the mathematical ideas and biological processes are made clear, the book reflects the irreversible trend of increasing mathematical content in biology education. Therefore to assist both teacher and student, in an associated website Palsson provides problem sets, projects and Powerpoint slides, and keeps the presentation in the book concrete with illustrative material and experimental results. |
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Inhalt
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Systems Biology: Properties of Reconstructed Networks Bernhard Palsson Keine Leseprobe verfügbar - 2006 |
Häufige Begriffe und Wortgruppen
activity allowable analysis approach associated basic basis vectors binding biochemical biological biomass cell cellular Chapter chemical coli column combination complex components compounds computed concentration connected conservation constraints contains convex core corresponding defined described detailed determine developed distribution elementary reactions elements enzyme equation example exchange expression extreme pathways factor Figure flux four function fundamental gene genetic genome genome-scale give given glucose growth illustrated important inputs interactions lead left null space linear mathematical metabolic network metabolites methods models molecules NADH nature Note objective function optimal organisms outputs participation particular phenotypic points pools production properties protein range reaction networks reconstruction regulation regulatory networks representation represents result sampling sequence shown shows signaling signaling networks silico simple singular solution space stoichiometric matrix structure substrate Table tion transcription types uptake values variables
Beliebte Passagen
Seite 13 - Mathematical modeling and analysis in biochemical engineering: past accomplishments and future opportunities,