Abstract
In this paper, a multi-channel multi-dimensional approach is investigated for modeling of signals obtained from DNA gel electrophoresis. Related applications include DNA fingerprinting and crime scene investigations. In order to improve resolution and accuracy of modeling, a novel approach is employed based on using equidistant multi-capture data frames obtained over an extended span of time. The multidimensional signal is rescaled and aligned which improves resolution, then the signal is modeled as a surface that varies with both the time index and separation size. The overall approach is tested on a number of datasets. The simulation results show that the proposed approach can be used as a starting multi-dimensional time series model for raw signals obtained from gel electrophoresis.
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