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                                       Details for article 10 of 11 found articles
 
 
  Using Amino Acid Patterns to Accurately Predict Translation Initiation Sites
 
 
Title: Using Amino Acid Patterns to Accurately Predict Translation Initiation Sites
Author: Huiqing Liu
Hao Han
Jinyan Li
Limsoon Wong
Appeared in: In silico biology
Paging: Volume 4 (2004) nr. 3 pages 255-269
Year: 2004-12-01
Contents: The translation initiation site (TIS) prediction problem is about how to correctly identify TIS in mRNA, cDNA, or other types of genomic sequences. High prediction accuracy can be helpful in a better understanding of protein coding from nucleotide sequences. This is an important step in genomic analysis to determine protein coding from nucleotide sequences. In this paper, we present an in silico method to predict translation initiation sites in vertebrate cDNA or mRNA sequences. This method consists of three sequential steps as follows. In the first step, candidate features are generated using k-gram amino acid patterns. In the second step, a small number of top-ranked features are selected by an entropy-based algorithm. In the third step, a classification model is built to recognize true TISs by applying support vector machines or ensembles of decision trees to the selected features. We have tested our method on several independent data sets, including two public ones and our own extracted sequences. The experimental results achieved are better than those reported previously using the same data sets. Our high accuracy not only demonstrates the feasibility of our method, but also indicates that there might be "amino acid" patterns around TIS in cDNA and mRNA sequences.
Publisher: IOS Press
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 10 of 11 found articles
 
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