Learning gene regulation from microarray data via Hidden Markov Models. Abali, A. O., Erzin, E., & Guersoy, A. In 2007 IEEE 15TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS, VOLS 1-3, pages 71-74, 2007. IEEE. IEEE 15th Signal Processing and Communications Applications Conference, Eskisehir, TURKEY, JUN 11-13, 2007abstract bibtex An important problem in computational biology is prediction of gene regulatory networks. There are many approaches to this problem. However Hidden Markov Models that are known to show high performance in signal similarity related uses are hard to come by in literature [1]. We have shown through our investigations that this method outperforms Correlation method. Furthermore, it is clear that this method can be improved to achieve even higher performance. Hidden Markov Models are a reasonable candidate in becoming a useful tool in predicting gene regulatory networks.
@inproceedings{ ISI:000252924600019,
Author = {Abali, Ali Oezguer and Erzin, Engin and Guersoy, Attila},
Book-Group-Author = {{IEEE}},
Title = {{Learning gene regulation from microarray data via Hidden Markov Models}},
Booktitle = {{2007 IEEE 15TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS, VOLS
1-3}},
Year = {{2007}},
Pages = {{71-74}},
Note = {{IEEE 15th Signal Processing and Communications Applications Conference,
Eskisehir, TURKEY, JUN 11-13, 2007}},
Organization = {{IEEE}},
Abstract = {{An important problem in computational biology is prediction of gene
regulatory networks. There are many approaches to this problem. However
Hidden Markov Models that are known to show high performance in signal
similarity related uses are hard to come by in literature {[}1]. We have
shown through our investigations that this method outperforms
Correlation method. Furthermore, it is clear that this method can be
improved to achieve even higher performance. Hidden Markov Models are a
reasonable candidate in becoming a useful tool in predicting gene
regulatory networks.}},
ISBN = {{978-1-4244-0719-4}},
ResearcherID-Numbers = {{Erzin, Engin/H-1716-2011
Gursoy, Attila/E-9565-2015}},
ORCID-Numbers = {{Erzin, Engin/0000-0002-2715-2368
Gursoy, Attila/0000-0002-2297-2113}},
Unique-ID = {{ISI:000252924600019}},
}
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