We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Predicting Secondary Structure of Protein Using Hybrid of Convolutional Neural Network and Support Vector Machine.
- Authors
Sutanto, Vincent Michael; Sukma, Zaki Indra; Afiahayati, Afiahayati
- Abstract
Protein secondary structure prediction is one of the problems in the Bioinformatics field, which conducted to find the function of proteins. Protein secondary structure prediction is done by classifying each sequence of protein primary structure into the sequence of protein secondary structure, which fall in sequence labelling problems and can be solved with the machine learning. Convolutional Neural Network (CNN) and Support Vector Machine (SVM) are 2 methods that often used to solve classification problems. In this research, we proposed a hybrid of 1-Dimensional CNN and SVM to predict the secondary structure of the protein. In this research, we used a novel hybrid 1-Dimensional CNN and SVM for sequence labelling, specifically to predict the secondary structure of the protein. Our hybrid model managed to outperform previous studies in term of Q3 and Q8 accuracy on CB513 dataset.
- Subjects
PROTEIN structure; CONVOLUTIONAL neural networks; SUPPORT vector machines; AMINO acid sequence; MACHINE learning
- Publication
International Journal of Intelligent Engineering & Systems, 2021, Vol 14, Issue 1, p232
- ISSN
2185-310X
- Publication type
Article
- DOI
10.22266/ijies2021.0228.23