Abstract
The amount of available genomic DNA sequence data is growing at an enormous rate. The analysis of these DNA sequences currently becomes a hot topic. One major problem is the prediction of splice site locations, which is related to the identification of a gene. The splicing is an important process occurring in the post-transcriptional phase, and is required to remove the introns. In this thesis, we employ the log-linear graphical model to predict the splice sites. With the help of the iterative proportional scaling algorithm, we are able to find the the maximum likelihood estimation based on the log-linear model. Then we apply our method to predict the splice site of DNA coding sequences from two species human and fly. Results obtained through 5-fold cross-validation tests show that with 10% false negative rate, our model can reach about 95% to 97% specificity for donor site prediction and 85% to 93% for acceptor site prediction.