Protein-RNA interaction prediction using graphical representation of biological sequences
| dc.authorscopusid | 57217207064 | |
| dc.contributor.author | Dogan B. | |
| dc.date.accessioned | 2024-08-04T20:04:01Z | |
| dc.date.available | 2024-08-04T20:04:01Z | |
| dc.date.issued | 2019 | |
| dc.department | İnönü Üniversitesi | en_US |
| dc.description | 27th Signal Processing and Communications Applications Conference, SIU 2019 -- 24 April 2019 through 26 April 2019 -- 151073 | en_US |
| dc.description.abstract | Protein-RNA interactions play a crucial role in posttranscriptional regulation of gene expression and have diverse functions in various biological processes. Therefore, identification of protein-RNA interactions is quite important. Experimental methods used for this purpose are expensive, time-consuming and labor intensive. Alternatively, machine learning based methods are proposed to detect protein-RNA interactions computationally. In these methods, each protein-RNA pair is represented by a feature vector which is then used to train machine learning methods. Here, in this study, we also proposed an alternative method to form a feature vector for each protein-RNA pair. Compared to the existing methods, the proposed method creates low-dimensional feature vectors which in turn decreases the overall computational time required to train and test the machine learning methods. Moreover, the proposed method does not make any concession on the classification performance. © 2019 IEEE. | en_US |
| dc.identifier.doi | 10.1109/SIU.2019.8806484 | |
| dc.identifier.isbn | 9781728119045 | |
| dc.identifier.scopus | 2-s2.0-85071963470 | en_US |
| dc.identifier.scopusquality | N/A | en_US |
| dc.identifier.uri | https://doi.org/10.1109/SIU.2019.8806484 | |
| dc.identifier.uri | https://hdl.handle.net/11616/92293 | |
| dc.indekslendigikaynak | Scopus | en_US |
| dc.language.iso | tr | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
| dc.relation.ispartof | 27th Signal Processing and Communications Applications Conference, SIU 2019 | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Conjoint-triad method | en_US |
| dc.subject | Machine learning | en_US |
| dc.subject | Protein-RNA interaction | en_US |
| dc.subject | RNA-binding proteins | en_US |
| dc.title | Protein-RNA interaction prediction using graphical representation of biological sequences | en_US |
| dc.title.alternative | Biyolojik Sekanslarin Grafik Temsili ile Protein-RNA Etkileşimi Tahmini | en_US |
| dc.type | Conference Object | en_US |
