Optimization of receptor-channel kinetics project

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A short lead paragraph

Contents

Objective

The focus of our study is to leverage massive parallelism in advanced computer systems to simulate and model ion channel kinetics, specifically as related to AMPA receptors. Scientists simulate the kinetics of ion channels to investigate how different inputs (e.g. for AMPARs, the alteration of the relative amount and temporal characteristics of glutamate stimulation) influence reaction rates and transition states of the kinetic scheme. Previously published kinetic schemes are unable to simultaneously describe several features including the effects of partial agonists on channel conductance and related shifts in conductance due to phosphorylation which preserve affinity and densensitization/deactivation. Our target application, Kingen, was developed to simulate AMPAR ion channel activity and to optimize kinetic model rate constants to biological data. Kingen uses a genetic algorithm to stochastically search parameter space to find global optima. As each individual in the population describes a rate constant parameter set in the kinetic model and the model is evaluated for each individual, there is significant computational complexity and parallelism in even a simple model run. This work enables rapid design of complicated kinetic models that more accurately represent what occurs in nature that could not be considered before due to computational limitations.

Major results

Project lead

Tim Benke

Users

  • Allison Gehrke, PhD Student, Department of Computer Science, University of Colorado, Denver

Funding

Epilepsy Foundation and NIH/NINDS

ARCS - Achievement Rewards for College Scientists [1]

Recent publications

Journal articles

Conferences

A. Gehrke and D. Connors and I. Ra, A Framework for Automated Performance Tuning and Code Verification on GPU Computing Platforms, The 25th IEEE International Parallel and Distributed Processing Symposium (IPDPS), May 16-20, 2011, Anchorage, U.S.A (Accepted for poster presentation at PhD forum and printed for publication)

Allison Gehrke, Katherine Rennie, Timothy Benke, Daniel A. Connors, and Ilkyeun Ra. Modeling ion channel kinetics with HPC. High Performance Computing and Communications, 10th IEEE International Conference on, 0:562–567, 2010.

External links

Links to project's websites

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