title: Eukaryotic gene prediction using GeneMark.hmm.
abstract: In this unit, eukaryotic GeneMark.hmm is presented as a method for detecting genes in eukaryotic DNA sequences. The eukaryotic GeneMark.hmm uses Markov models of protein coding and noncoding sequences, as well as positional nucleotide frequency matrices for prediction of the translational start, translational termination and splice sites. All these models along with length distributions of exons, introns and intergenic regions are integrated into one Hidden Markov model. The unit describes running the program over the Internet and locally on a Unix machine. It also discusses GeneMarkS EV, which can be used to detect genes in eukaryotic viruses.
authors.affiliation: School of Biology and School of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
authors.forename: Mark
authors.initials: M
authors.lastname: Borodovsky
authors.forename: Alex
authors.initials: A
authors.lastname: Lomsadze
authors.forename: Nikolai
authors.initials: N
authors.lastname: Ivanov
authors.forename: Ryan
authors.initials: R
authors.lastname: Mills
mesh_terms: D000465:Algorithms; D000818:Animals; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D005057:Eukaryotic Cells / Q000502:physiology*; D006801:Humans; D008390:Markov Chains; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated / Q000379:methods; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software