| Title | Computational Approaches to Gene Prediction |
|---|---|
| Author | Jin Hwan Do1 and Dong-Kug Choi2,* |
| Address | 1Bio-food and Drug Research Center, Konkuk University, Chungju, 380-701, Republic of Korea, 2Department of Biotechnology, Konkuk University, Chungju, 380-701, Republic of Korea |
| Bibliography | Journal of Microbiology, 44(2),137-144, 2006, |
| DOI | |
| Key Words | gene prediction, signal/content sensors, similarity-based, gene-finders, ab initio gene-finders |
| Abstract | The problems associated with gene identification and the prediction of gene structure in DNA sequences have been the focus of increased attention over the past few years with the recent acquisition by large-scale sequencing projects of an immense amount of genome data. A variety of prediction programs have been developed in order to address these problems. This paper presents a review of the computational approaches and gene-finders used commonly for gene prediction in eukaryotic genomes. Two approaches, in general, have been adopted for this purpose: similarity-based and ab initio techniques. The information gleaned from these methods is then combined via a variety of algorithms, including Dynamic Programming (DP) or the Hidden Markov Model (HMM), and then used for gene prediction from the genomic sequences. |
| Download PDF | 02 JM2005-152.pdf |