Duration learning for analysis of nanopore ionic current blockades

Background: Ionic current blockade signal processing, for use in nanopore detection, offers a promising new way to analyze single molecule properties, with potential implications for DNA sequencing. The alpha-Hemolysin transmembrane channel interacts with a translocating molecule in a nontrivial way, frequently evidenced by a complex ionic flow blockade pattern. Typically, recorded current blockade signals have several levels of blockade, with various durations, all obeying a fixed statistical profile for a given molecule. Hidden Markov Model (HMM) based duration learning experiments on artificial two-level Gaussian blockade signals helped us to identify proper modeling framework. We then apply our framework to the real multi-level DNA hairpin blockade signal. Results: The identified upper level blockade state is observed with durations that are geometrically distributed (consistent with an a physical decay process for remaining in any given state). We show that mixture of convolution...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Alexander G. Churbanov, Carl Baribault, Stephen Winters-Hilt
• Keywords: Blockade, BMCBI 2007, Current Blockade Signal, Ionic Current Blockade