Postdoctoral Research Fellowships in Biology for FY 2009 View Homepage


Ontology type: schema:MonetaryGrant     


Grant Info

YEARS

2009-2011

FUNDING AMOUNT

123000 USD

ABSTRACT

This action funds an NSF Postdoctoral Research Fellowship for FY 2009. The fellowship supports a research and training plan entitled "Characterizing the molecular basis of muscle contraction using a white-noise method of system analysis" for Bertrand Tanner. The host institution for this research is the University of Vermont, and the sponsoring scientist is David Maughan. Biological systems generally exhibit complicated behavior driven by underlying spatial, chemical, and mechanical processes. This research develops and applies engineering techniques of system analysis to identify and describe molecular processes that underlie contraction in muscle tissue. This technique uses small, random changes in muscle length (white-noise length stimuli) to distinguish linear and non-linear portions of the muscle response. Specifically, this research utilizes flight muscle fibers stripped of their cellular membranes to allow control of their chemical environment. This methodology will facilitate measurements over a physiological range of muscle distortions, while simultaneously sampling a broader frequency range of the muscle response than is available with current measurement techniques. These proposed measurements will reveal dynamic properties of invertebrate muscle in unprecedented detail, and set the stage for applying white-noise analysis to vertebrate muscle and other biological systems. The training goals are development of computational tools used to predict complex biological behavior and for study of biomechanics. Broader impacts of this work include training undergraduate students to use mathematical models to study muscle contraction. This research provides a basic framework for study of biomechanical systems at various levels, from individual molecules to entire organisms. More... »

URL

http://www.nsf.gov/awardsearch/showAward?AWD_ID=0905830&HistoricalAwards=false

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