With more states revealed, and more reliable rates inferred, mechanistic schemes for ion channels have increased in complexity over the history of single-channel studies. At the forefront of single-channel studies we are faced with a temporal barrier delimiting the briefest event which can be detected in single-channel data. Despite improvements in single-channel data analysis, the use of existing methods remains sub-optimal. As existing methods in single-channel data analysis are unquantified, optimal conditions for data analysis are unknown. Here we present a modular single-channel data simulator with two engines; a Hidden Markov Model (HMM) engine, and a sampling engine. The simulator is a tool which provides the necessary a priori information to be able to quantify and compare existing methods in order to optimize analytic conditions. We demonstrate the utility of our simulator by providing a preliminary comparison of two event detection methods in single-channel data analysis; Threshold Crossing and Segmental k-means with Hidden Markov Modelling (SKM-HMM).
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/39729 |
| Date | 16 October 2019 |
| Creators | Dextraze, Mathieu Francis |
| Contributors | daCosta, Corrie John Bayley |
| Publisher | Université d'Ottawa / University of Ottawa |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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