04374nam 22007455 450 991030036910332120200706185030.03-319-00744-010.1007/978-3-319-00744-1(CKB)3710000000025633(EBL)1538882(SSID)ssj0001049527(PQKBManifestationID)11592866(PQKBTitleCode)TC0001049527(PQKBWorkID)11019465(PQKB)10749410(MiAaPQ)EBC1538882(DE-He213)978-3-319-00744-1(PPN)176103325(EXLCZ)99371000000002563320131008d2014 u| 0engur|n|---|||||txtccrMathematical Modelling of the Cell Cycle Stress Response /by Elahe Radmaneshfar1st ed. 2014.Cham :Springer International Publishing :Imprint: Springer,2014.1 online resource (122 p.)Springer Theses, Recognizing Outstanding Ph.D. Research,2190-5053Description based upon print version of record.3-319-00743-2 Includes bibliographical references.A biological overview of the cell cycle and its response to osmotic stress and the α-factor -- ODE model of the cell cycle response to osmotic stress -- Boolean model of the cell cycle response to stress -- Conclusion -- List of equations, parameters and initial conditions -- Effect of methods of update on existence of fixed points.The cell cycle is a sequence of biochemical events that are controlled by complex but robust molecular machinery. This enables cells to achieve accurate self-reproduction under a broad range of conditions. Environmental changes are transmitted by molecular signaling networks, which coordinate their actions with the cell cycle.   This work presents the first description of two complementary computational models describing the influence of osmotic stress on the entire cell cycle of S. cerevisiae. Our models condense a vast amount of experimental evidence on the interaction of the cell cycle network components with the osmotic stress pathway. Importantly, it is only by considering the entire cell cycle that we are able to make a series of novel predictions which emerge from the coupling between the molecular components of different cell cycle phases.   The model-based predictions are supported by experiments in S. cerevisiae and, moreover, have recently been observed in other eukaryotes. Furthermore our models reveal the mechanisms that emerge as a result of the interaction between the cell cycle and stress response networks.Springer Theses, Recognizing Outstanding Ph.D. Research,2190-5053BiophysicsBiological physicsCell cycleBiomathematicsBioinformaticsPhysicsBiological and Medical Physics, Biophysicshttps://scigraph.springernature.com/ontologies/product-market-codes/P27008Cell Cycle Analysishttps://scigraph.springernature.com/ontologies/product-market-codes/L16030Physiological, Cellular and Medical Topicshttps://scigraph.springernature.com/ontologies/product-market-codes/M31020Computational Biology/Bioinformaticshttps://scigraph.springernature.com/ontologies/product-market-codes/I23050Applications of Graph Theory and Complex Networkshttps://scigraph.springernature.com/ontologies/product-market-codes/P33010Biophysics.Biological physics.Cell cycle.Biomathematics.Bioinformatics.Physics.Biological and Medical Physics, Biophysics.Cell Cycle Analysis.Physiological, Cellular and Medical Topics.Computational Biology/Bioinformatics.Applications of Graph Theory and Complex Networks.570.285Radmaneshfar Elaheauthttp://id.loc.gov/vocabulary/relators/aut791337BOOK9910300369103321Mathematical Modelling of the Cell Cycle Stress Response1768715UNINA