Single biopolymers (DNA, RNA, or polypeptide) can be examined using an alpha-hemolysin channel detector. When a biopolymer is present in an alpha-hemolysin channel it can produce a highly structured ionic current blockade pattern, where the lifetimes at various sub-blockade levels reveal information about the kinetics of the biopolymer. Here we describe integration of LabVIEW/LabWindows automation capabilities with the in-house Channel Current Cheminformatics (CCC) software. Data acquired with LabVIEW/LabWindows is passed to the CCC software, on a streaming real time basis, for analysis and classification. The classification results are then quickly returned to the LabVIEW/LabWindows automation software for experimental feedback control. The prototype signal processing architecture is designed to rapidly extract useful information from noisy blockade signals. A fast, specially designed, generic Hidden Markov Model can be used for the channel current feature extraction. Classification of feature vectors obtained by the HMM can then be done by Support Vector Machines
