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IEEE Computer Society Bioinformatics Conference (CSB'03)
Estimating Recombination Rate Distribution by Optimal Quantization
Stanford, California
August 11-August 14
ISBN: 0-7695-2000-6
Mingzhou Song, Queens College
Stephane Boissinot, Queens College
Robert M. Haralick, City University of New York
Ihsin T. Phillips, Queens College
We obtain recombination rate distribution functions for all human chromosomes using an optimal quantization method. This non-parametric method allows us to control over-/under-fitting. The piece-wise constant recombination rate distribution functions are convenient to store and retrieve. Our experimental results showed more abrupt distribution functions than two recently published results. In the previous results, the over-/under-fitting issues were not addressed explicitly. Our estimation had greater log likelihood over a previous result using Parzen window. It suggests that the optimal quantization technique might be of great advantage for estimation of other genomic feature distributions.
Citation:
Mingzhou Song, Stephane Boissinot, Robert M. Haralick, Ihsin T. Phillips, "Estimating Recombination Rate Distribution by Optimal Quantization," csb, pp.403, IEEE Computer Society Bioinformatics Conference (CSB'03), 2003
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