Title

Translation initiation sites prediction with mixture gaussian models

Publication Type

Book Chapter

Publication Date

12-2004

Abstract

Translation initiation sites (TIS) are important signals in cDNA sequences. Many research efforts have tried to predict TIS in cDNA sequences. In this paper, we propose using mixture Gaussian models to predict TIS in cDNA sequences. Some new global measures are used to generate numerical features from cDNA sequences, such as the length of the open reading frame downstream from ATG, the number of other ATGs upstream and downstream from the current ATGs, etc. With these global features, the proposed method predicts TIS with sensitivity 98% and specificity 92%. The sensitivity is much better than that from other methods. We attribute the improvement in sensitivity to the nature of the global features and the mixture Gaussian models. © Springer-Verlag 2004.

Keywords

Artificial intelligence, Bioinformatics, Forecasting, Mixtures, Numerical methods, Translation (languages), cDNA sequence, Global feature, Global measures, Mixture Gaussian model, Numerical features, Open reading frame, Research efforts, Translation initiation site

Discipline

Numerical Analysis and Scientific Computing

Publication

Algorithms in Bioinformatics: 4th International Workshop, WABI 2004, Bergen, Norway, September 17-21, 2004. Proceedings

Volume

3240

Editor

Inge Jonassen, Junhyong Kim

First Page

338

Last Page

349

ISBN

9783540230182

Identifier

10.1007/978-3-540-30219-3_29

Publisher

Springer

City or Country

NewYork

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