Multiscale Models of Cell Signaling
نویسندگان
چکیده
منابع مشابه
Models of cell signaling pathways.
Cellular signaling circuits handle an enormous range of computations. Beyond the housekeeping, replicating and other functions of individual cells, signaling circuits must implement the immensely complex logic of development and function of multicellular organisms. Computer models are useful tools to understand this complexity. Recent studies have extended such models to include electrical, mec...
متن کاملBioengineering models of cell signaling.
Strategies for rationally manipulating cell behavior in cell-based technologies and molecular therapeutics and understanding effects of environmental agents on physiological systems may be derived from a mechanistic understanding of underlying signaling mechanisms that regulate cell functions. Three crucial attributes of signal transduction necessitate modeling approaches for analyzing these sy...
متن کاملCell mechanics: from single scale-based models to multiscale modelling
Biological cells are considered as the building units of life. It was Robert Hooke who coined the word cell in histological description of cork and other specimens using coarse optical lenses, as published in his Micrographia in 1665 [10]. A few years later, Anthonie van Leeuwenhoek used a self-built microscope to observe living microorganisms which he called animalcules ('little ani-mals') whi...
متن کاملMathematical models of specificity in cell signaling.
Cellular signaling pathways transduce extracellular signals into appropriate responses. These pathways are typically interconnected to form networks, often with different pathways sharing similar or identical components. A consequence of this connectedness is the potential for cross talk, some of which may be undesirable. Indeed, experimental evidence indicates that cells have evolved insulatin...
متن کاملMultiscale Sparse Microcanonical Models
We study density estimation of stationary processes defined over an infinite grid from a single, finite realization. Gaussian Processes and Markov Random Fields avoid the curse of dimensionality by focusing on low-order and localized potentials respectively, but its application to complex datasets is limited by their inability to capture singularities and long-range interactions, and their expe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Annals of Biomedical Engineering
سال: 2012
ISSN: 0090-6964,1573-9686
DOI: 10.1007/s10439-012-0560-1