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dc.contributor.authorJain, Shruti-
dc.contributor.authorNaik, P.K.-
dc.contributor.authorBhooshan, Sunil V.-
dc.descriptionDigest Journal of Nanomaterials and Biostructures Vol. 5, No 1, March 2010, p. 57 - 66en_US
dc.description.abstractSystems Biology is the science of discovering, modeling, understanding and ultimately engineering at the molecular level the dynamic relationships between the biological molecules that define living organisms. Computational modeling is useful as a means to assemble and test what we know about proteins and networks. Models can help address key questions about the measurement, definition and function. Computationally intensive simulations can incorporate greater numbers of neurons to model increasingly complex and realistic properties, both electrical and chemical. Recent studies suggest that the balance between cell survival signals and pro-apoptotic stimuli controls the decision between cell repair and death. Inspired by the computational feasibility of Simulation Program For Integrated Circuit Emphasis (SPICE), and Ladder logic we set out to build a systematic signaling network that would enable the predictive signal of cell death/ survival given Tumor necrosis factor-α (TNF), Epidermal growth factor (EGF) and Insulin as inputs. We conclude that it is possible to build self consistent prediction model that can be computationally to yield important insights into the control of cell death/ survival responses.en_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectTumor necrosis factor-α,en_US
dc.subjectEpidermal growth factoren_US
dc.titleA System Model for Cell Death Survival Using Spice and Ladder Logicen_US
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