Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
Discrete Applied Mathematics - Special volume on combinatorial molecular biology
Modelling electropherogram data for DNA sequencing using variable dimension MCMC
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06
Computer-aided DNA base calling from forward and reverse electropherograms
Transactions on Computational Systems Biology III
Fast and robust fixed-point algorithms for independent component analysis
IEEE Transactions on Neural Networks
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In automated DNA sequencing, the final algorithmic phase, referred to as basecalling, consists of the translation of four time signals in the form of peak sequences (electropherogram) to the corresponding sequence of bases. Commercial basecallers detect the peaks based on heuristics, and are very efficient when the peaks are distinct and regular in spread, amplitude and spacing. Unfortunately, in the practice the signals are subject to several degradations, among which peak superposition and peak merging are the most frequent. In these cases the experiment must be repeated and human intervention is required. Recently, there have been attempts to provide methodological foundations to the problem and to use statistical models for solving it. In this paper, we exploit a priori information and Bayesian estimation to remove degradations and recover the signals in an impulsive form which makes basecalling straightforward.