TY - GEN
T1 - A generalized hidden Markov model for prediction of cis-regulatory modules in eukaryote genomes and description of their internal structure
AU - Nilulova, Anna A.
AU - Favorov, Alexander V.
AU - Makeev, Vsevolod Yu
AU - Mironov, Andrey A.
PY - 2012/6/13
Y1 - 2012/6/13
N2 - Eukaryotic regulatory regions have been studied extensively due to their importance for gene regulation in higher eukaryotes. However, the understanding of their organization is clearly incomplete. In particular, we lack accurate in silico methods for their prediction. Here we present a new HMM-based method for the prediction of regulatory regions in eukaryotic genomes using position weight matrices of the relevant transcription factors. The method reveals and then utilizes the regulatory region structure (preferred binding site arrangements) to increase the quality of the prediction, as well as to provide a new knowledge of the regulatory region organization. We show that our method can be successfully used for the identification of regulatory regions in eukaryotic genomes with a quality higher than that of other methods. We also demonstrate the ability of our algorithm to reveal structural features of the regulatory regions, which could be helpful for the deciphering of the transcriptional regulation mechanisms in higher eukaryotes.
AB - Eukaryotic regulatory regions have been studied extensively due to their importance for gene regulation in higher eukaryotes. However, the understanding of their organization is clearly incomplete. In particular, we lack accurate in silico methods for their prediction. Here we present a new HMM-based method for the prediction of regulatory regions in eukaryotic genomes using position weight matrices of the relevant transcription factors. The method reveals and then utilizes the regulatory region structure (preferred binding site arrangements) to increase the quality of the prediction, as well as to provide a new knowledge of the regulatory region organization. We show that our method can be successfully used for the identification of regulatory regions in eukaryotic genomes with a quality higher than that of other methods. We also demonstrate the ability of our algorithm to reveal structural features of the regulatory regions, which could be helpful for the deciphering of the transcriptional regulation mechanisms in higher eukaryotes.
KW - Binding sites
KW - Cis-regulatory modules
KW - Eukaryotes
KW - Generalized hidden Markov models
KW - Regulation of transcription
KW - Regulatory structure
UR - http://www.scopus.com/inward/record.url?scp=84861978902&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84861978902&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84861978902
SN - 9789898425904
T3 - BIOINFORMATICS 2012 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms
SP - 34
EP - 41
BT - BIOINFORMATICS 2012 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms
T2 - International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2012
Y2 - 1 February 2012 through 4 February 2012
ER -