Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/2035
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Özyer, Tansel | - |
dc.contributor.author | Alhajj, Reda | - |
dc.date.accessioned | 2019-07-10T14:42:47Z | |
dc.date.available | 2019-07-10T14:42:47Z | |
dc.date.issued | 2017-10-20 | |
dc.identifier.citation | Özyer, T., & Alhajj, R. (2017, May). A comprehensive approach for validating p53 binding site predictions. In 2017 8th International Conference on Information Technology (ICIT) (pp. 846-853). IEEE. | en_US |
dc.identifier.isbn | 978-150906332-1 | |
dc.identifier.uri | https://ieeexplore.ieee.org/document/8079957 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/2035 | - |
dc.description | 8th International Conference on Information Technology (2017 : Amman; Jordan) | |
dc.description.abstract | Predicting the locations of Response Elements (RE) has received considerable attention in the field of gene sequence analysis and bioinformatics. Protein53 (p53) has a prominent role in the cell cycle and cancer prevention; it functions as a transcription factor and binds with p53 REs in the DNA. The identification of p53 response elements enlightens the unknown functions and characteristics of p53 besides the genes containing binding sites. In this work, we have proposed an algorithm for validating the prediction of the possible p53 binding sites in the human genome, by incorporating the recent findings on the p53 REs into our suggested profile hidden Markov model (PHMM). We constructed two PHMMs and the results described in this paper are very promising. In the experiments, we have used the p53 REs data reported by Riley et al. [21]. © 2017 IEEE. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation.ispartof | ICIT 2017 - 8th International Conference on Information Technology, Proceedings | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Neoplasms | en_US |
dc.subject | Tumor Suppressor Protein p53 | en_US |
dc.subject | p53 proteins | en_US |
dc.title | A Comprehensive Approach for Validating P53 Binding Site Predictions | en_US |
dc.type | Conference Object | en_US |
dc.department | Faculties, Faculty of Engineering, Department of Computer Engineering | en_US |
dc.department | Fakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | tr_TR |
dc.identifier.startpage | 846 | |
dc.identifier.endpage | 853 | |
dc.identifier.scopus | 2-s2.0-85040021851 | en_US |
dc.institutionauthor | Özyer, Tansel | - |
dc.identifier.doi | 10.1109/ICITECH.2017.8079957 | - |
dc.authorscopusid | 8914139000 | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
item.openairetype | Conference Object | - |
item.languageiso639-1 | en | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | 02.1. Department of Artificial Intelligence Engineering | - |
Appears in Collections: | Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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