摘要
Although disease diagnosis have greatly benefited from next generation sequencing technologies, it is still difficult to make the right diagnosis based on purely sequencing technologies for many diseases with complex phenotypes and high genetic heterogeneity. Recently, calculating Human Phenotype Ontology (HPO)-based phenotype semantic similarity has contributed a lot for completing disease diagnosis. However, factors which affect the accuracy of HPO-based semantic similarity have not been evaluated systematically. In this study, we propose a new framework called HPOFactor to evaluate these factors.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 |
| 编辑 | Kevin Burrage, Qian Zhu, Yunlong Liu, Tianhai Tian, Yadong Wang, Xiaohua Tony Hu, Qinghua Jiang, Jiangning Song, Shinichi Morishita, Kevin Burrage, Guohua Wang |
| 出版商 | Institute of Electrical and Electronics Engineers Inc. |
| 页 | 1653-1656 |
| 页数 | 4 |
| ISBN(电子版) | 9781509016105 |
| DOI | |
| 出版状态 | 已出版 - 17 1月 2017 |
| 活动 | 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 - Shenzhen, 中国 期限: 15 12月 2016 → 18 12月 2016 |
出版系列
| 姓名 | Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 |
|---|
会议
| 会议 | 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 |
|---|---|
| 国家/地区 | 中国 |
| 市 | Shenzhen |
| 时期 | 15/12/16 → 18/12/16 |
联合国可持续发展目标
此成果有助于实现下列可持续发展目标:
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可持续发展目标 3 良好健康与福祉
学术指纹
探究 'Analyzing factors involved in the HPO-based semantic similarity calculation' 的科研主题。它们共同构成独一无二的学术指纹。引用此
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