Journal
INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS
Volume 13, Issue 3, Pages 211-224Publisher
INDERSCIENCE ENTERPRISES LTD
DOI: 10.1504/IJDMB.2015.072072
Keywords
human leukocyte antigen; support vector machine; physicochemical property; gene prediction
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Funding
- Office of the Higher Education Commission
- Mahidol University under the National Research Universities Initiative
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Prediction of different classes within the human leukocyte antigen (HLA) gene family can provide insight into the human immune system and its response to viral pathogens. Therefore, it is desirable to develop an efficient and easily interpretable method for predicting HLA gene class compared to existing methods. We investigated the HLA gene prediction problem as follows: (a) establishing a dataset (HLA262) such that the sequence identity of the complete HLA dataset was reduced to 30%; (b) proposing a feature set of informative physicochemical properties that cooperate with SVM (named HLAPred) to achieve high accuracy and sensitivity (90.04% and 82.99%, respectively) compared with existing methods; and (c) analysing the informative physicochemical properties to understand the physicochemical properties and molecular mechanisms of the HLA gene family.
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