Publication: Sequence based human leukocyte antigen gene prediction using informative physicochemical properties
Issued Date
2015-01-01
Resource Type
ISSN
17485681
17485673
17485673
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2-s2.0-84943425242
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Mahidol University
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SCOPUS
Bibliographic Citation
International Journal of Data Mining and Bioinformatics. Vol.13, No.3 (2015), 211-224
Suggested Citation
Watshara Shoombuatong, Panuwat Mekha, Jeerayut Chaijaruwanich Sequence based human leukocyte antigen gene prediction using informative physicochemical properties. International Journal of Data Mining and Bioinformatics. Vol.13, No.3 (2015), 211-224. doi:10.1504/IJDMB.2015.072072 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/35622
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Title
Sequence based human leukocyte antigen gene prediction using informative physicochemical properties
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Abstract
Copyright © 2015 Inderscience Enterprises Ltd. 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.