title: A Review of Computational Intelligence Methods for Eukaryotic Promoter Prediction.
abstract: In past decades, prediction of genes in DNA sequences has attracted the attention of many researchers but due to its complex structure it is extremely intricate to correctly locate its position. A large number of regulatory regions are present in DNA that helps in transcription of a gene. Promoter is one such region and to find its location is a challenging problem. Various computational methods for promoter prediction have been developed over the past few years. This paper reviews these promoter prediction methods. Several difficulties and pitfalls encountered by these methods are also detailed, along with future research directions.
authors.affiliation: a Department of Computer Science and Engineering , PEC University of Technology , Chandigarh , India.
authors.forename: Shailendra
authors.initials: S
authors.lastname: Singh
authors.forename: Sukhbir
authors.initials: S
authors.lastname: Kaur
authors.forename: Neelam
authors.initials: N
authors.lastname: Goel
mesh_terms: D001185:Artificial Intelligence; D019295:Computational Biology / Q000379:methods*; D056890:Eukaryota / Q000235:genetics*; D011401:Promoter Regions, Genetic
keywords: Gene; SVM; genomic DNA; neural network; promoter; transcription start site