Comparison of Machine Learning Classifiers for Protein Secondary Structure Prediction
| dc.contributor.author | Aydin, Zafer | |
| dc.contributor.author | Kaynar, Oguz | |
| dc.contributor.author | Gormez, Yasin | |
| dc.contributor.author | Isik, Yunus Emre | |
| dc.date.accessioned | 2024-10-26T17:59:53Z | |
| dc.date.available | 2024-10-26T17:59:53Z | |
| dc.date.issued | 2018 | |
| dc.department | Sivas Cumhuriyet Üniversitesi | |
| dc.description | 26th IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 02-05, 2018 -- Izmir, TURKEY | |
| dc.description.abstract | Three-dimensional structure prediction is one of the important problems in bioinformatics and theoretical chemistry. One of the most important steps in the three-dimensional structure prediction is the estimation of secondary structure. Due to rapidly growing databases and recent feature extraction methods datasets used for predicting secondary structure can potentially contain a large number of samples and dimensions. For this reason, it is important to use algorithms that are fast and accurate. In this study, various classification algorithms have been optimized for the second phase of a two-stage classifier on EVAset benchmark both in the original input space and in the space reduced using the information gain metric. The most accurate classifier is obtained as the support vector machine while the extreme learning machine is significantly faster in model training. | |
| dc.description.sponsorship | IEEE,Huawei,Aselsan,NETAS,IEEE Turkey Sect,IEEE Signal Proc Soc,IEEE Commun Soc,ViSRATEK,Adresgezgini,Rohde & Schwarz,Integrated Syst & Syst Design,Atilim Univ,Havelsan,Izmir Katip Celebi Univ | |
| dc.identifier.isbn | 978-1-5386-1501-0 | |
| dc.identifier.issn | 2165-0608 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12418/27388 | |
| dc.identifier.wos | WOS:000511448500400 | |
| dc.identifier.wosquality | N/A | |
| dc.indekslendigikaynak | Web of Science | |
| dc.language.iso | tr | |
| dc.publisher | IEEE | |
| dc.relation.ispartof | 2018 26th Signal Processing and Communications Applications Conference (Siu) | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | Secondary Structure Prediction | |
| dc.subject | Protein Structure Prediction | |
| dc.subject | Feature Selection | |
| dc.subject | Machine Learning | |
| dc.title | Comparison of Machine Learning Classifiers for Protein Secondary Structure Prediction | |
| dc.type | Conference Object |
