The prediction of the complete structure of genes is one of the very important 
tasks of bioinformatics, especially in eukaryotes. A crucial part in the gene 
structure prediction is to determine the splice sites in the coding region. 
Identification of splice sites depends on the precise recognition of the 
boundaries between exons and introns of a given DNA sequence. This problem can 
be formulated as a classification of sequence elements into 'exon-intron' (EI), 
'intron-exon' (IE) or 'None' (N) boundary classes. In this study we propose a 
new Weighted Position Specific Scoring Method (WPSSM) to recognize splice sites 
which uses a position-specific scoring matrix constructed by nucleotide base 
frequencies. A genetic algorithm is used in order to tune the weight and 
threshold parameters of the positions on. This method consists of two phases: 
learning phase and identification phase. The proposed WPSS method poses 
efficient results compared with the performance of many methods proposed in the 
literature. Computational experiments are performed on the DNA sequence datasets 
from 'UCI Repository of machine learning databases'.