EURASIP Journal on Applied Signal Processing
Volume 2001 (2001), Issue 4, Pages 297-303
doi:10.1155/S1110865701000270
On the Use of MDL Principle in Gene Expression Prediction
Signal Processing Laboratory, Tampere University of Technology, P.O. Box 553, Tampere SF-33101, Finland
Received 3 August 2001; Revised 28 September 2001
Abstract
The structure and biological behavior of a cell are
determined by the pattern of gene expressions within that cell.
The so-called gene prediction problem refers to finding rules, or
sets of possible rules, on how certain genes expressions
determine the expression level of a given target gene. In this
paper, we investigate the gene prediction problem and propose the
use of new predictors, selected according to the minimum
description length (MDL) principle. We compare the use of Boolean
predictors, ternary predictors and perceptron predictors. We
resort to MDL as a tool for selecting the proper size of the
prediction window. MDL is also well suited for comparing
predictors having different complexities. We show that the best
description can be achieved by the Boolean and ternary
predictors, since they obtain better fitting of the data with a
lower complexity of the model. To illustrate the comparison, both
synthetic and experimental data are used.