  Bioinformatics, as an emerging and rapidly developing interdisciplinary, has
become a promising and popular research field in 21st century. Extracting and
explaining useful biological information from huge amount of genetic data is an
urgent issue in post-genome era. In eukaryotic DNA sequences, gene consists of
exons and introns. To predict the location of exons which carry most genetic
information accurately has become one of the most essential issues in
bioinformatics. Here, we have used biological characteristics of introns to
find the candidate initial and final exon sections. Then we select candidate
exon sections by using Support Vector Machine (SVM). Next, we predict exon
sections accurately based on Discrete Fourier Transform (DFT) and using
three-base periodicity of DNA sequence signals. This paper provides a gene
prediction method based on statistics and signal processing and also, the
improvement and prospect for this method in the future are discussed.
