Translation initiation sites prediction with mixture gaussian models

Translation initiation sites prediction with mixture gaussian models

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 fr...

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Bibliographic Details
Main Authors: Li, Guoliang, Tze-Yun LEONG, Zhang, Louxin
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2004
Subjects:
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
Numerical Analysis and Scientific Computing
Online Access:https://ink.library.smu.edu.sg/sis_research/3050
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Institution: Singapore Management University
Language: English
Description
Summary: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.

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