An integrative approach to understanding mechanosensation
The ability for a living organism to sense and respond to its external environment is crucial to its survival. Understanding mechanosensation, the mechanism by which organisms react in response to mechanical stimuli, presents many interesting and challenging problems for both experimental and comput...
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Veröffentlicht in: | Briefings in bioinformatics 2007-07, Vol.8 (4), p.258-265 |
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description | The ability for a living organism to sense and respond to its external environment is crucial to its survival. Understanding mechanosensation, the mechanism by which organisms react in response to mechanical stimuli, presents many interesting and challenging problems for both experimental and computational biologists. A major difficulty in studying mechanosensors is their inherent multiscale nature. The systems involved in mechanosesnsing can span eight orders of magnitude in length scale and up to 10 orders of magnitude in time scale. Trying to ascertain information across these length and time scales simultaneously is challenging. This problem has led to the need to approach these types of problems using an integrative approach, combining both computational and experimental biology. This review classifies the major types of mechanosensors and explains methods that have been employed in understanding their behavior, both using modeling and experimental techniques. Multiscale modeling methods combined with experimental techniques in an integrative approach are suggested as ways of undertaking the study of such systems. |
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Understanding mechanosensation, the mechanism by which organisms react in response to mechanical stimuli, presents many interesting and challenging problems for both experimental and computational biologists. A major difficulty in studying mechanosensors is their inherent multiscale nature. The systems involved in mechanosesnsing can span eight orders of magnitude in length scale and up to 10 orders of magnitude in time scale. Trying to ascertain information across these length and time scales simultaneously is challenging. This problem has led to the need to approach these types of problems using an integrative approach, combining both computational and experimental biology. This review classifies the major types of mechanosensors and explains methods that have been employed in understanding their behavior, both using modeling and experimental techniques. 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Understanding mechanosensation, the mechanism by which organisms react in response to mechanical stimuli, presents many interesting and challenging problems for both experimental and computational biologists. A major difficulty in studying mechanosensors is their inherent multiscale nature. The systems involved in mechanosesnsing can span eight orders of magnitude in length scale and up to 10 orders of magnitude in time scale. Trying to ascertain information across these length and time scales simultaneously is challenging. This problem has led to the need to approach these types of problems using an integrative approach, combining both computational and experimental biology. This review classifies the major types of mechanosensors and explains methods that have been employed in understanding their behavior, both using modeling and experimental techniques. 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Understanding mechanosensation, the mechanism by which organisms react in response to mechanical stimuli, presents many interesting and challenging problems for both experimental and computational biologists. A major difficulty in studying mechanosensors is their inherent multiscale nature. The systems involved in mechanosesnsing can span eight orders of magnitude in length scale and up to 10 orders of magnitude in time scale. Trying to ascertain information across these length and time scales simultaneously is challenging. This problem has led to the need to approach these types of problems using an integrative approach, combining both computational and experimental biology. This review classifies the major types of mechanosensors and explains methods that have been employed in understanding their behavior, both using modeling and experimental techniques. 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subjects | Animals Bioinformatics Biology Experiments Finite Element Analysis Humans Integrated approach Ion Channels - physiology Mechanoreceptors - physiology Models, Biological Sensation - physiology Sensors Systems Integration |
title | An integrative approach to understanding mechanosensation |
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