Translation initiation sites prediction with mixture gaussian models

• 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
• Institution: Singapore Management University

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...