| 基于疾病本体的疾病相似性计算方法 |
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| 引用本文： | 李杰,初砚硕,程亮,王亚东,孔蕾蕾. 基于疾病本体的疾病相似性计算方法[J]. 生物化学与生物物理进展, 2015, 42(2): 115-122 |
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| 作者姓名： | 李杰 初砚硕 程亮 王亚东 孔蕾蕾 |
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| 作者单位： | 哈尔滨工业大学计算机科学与技术学院，哈尔滨 150001,哈尔滨工业大学计算机科学与技术学院，哈尔滨 150001,哈尔滨工业大学计算机科学与技术学院，哈尔滨 150001,哈尔滨工业大学计算机科学与技术学院，哈尔滨 150001,黑龙江工程学院计算机科学与技术学院，哈尔滨 150050 |
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| 基金项目： | 国家高技术研究发展计划(863)(2012AA02A602,2012AA020404),黑龙江省博士后科研发展基金(LBH-Q13084),哈尔滨市科技创新基金(2014RFQXJ090)和国家自然基金(61471147)资助项目 |
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| 摘 要： | 疾病相似性研究对于复杂疾病发病机制的理解、诊断、预测和药物研发具有重要意义.最近,研究人员通过集成多种疾病术语库,构建了描述疾病关系的疾病本体(disease ontology,DO),这为从DO角度研究疾病相似性打下了基础.本文综述了基于DO及其注释信息的疾病相似性计算方法,探讨了疾病相似性计算存在的问题和挑战,为疾病相似性进一步的研究提供有益参考.
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| 关 键 词： | 疾病本体 疾病相似性 |
| 收稿时间： | 2014-05-19 |
| 修稿时间： | 2014-08-24 |
Disease Ontology-based Methods for Disease Similarity Measurement |
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| LI JIE,CHU Yan-Shuo,CHENG Liang,WANG Ya-Dong and KONG Lei-Lei. Disease Ontology-based Methods for Disease Similarity Measurement[J]. Progress In Biochemistry and Biophysics, 2015, 42(2): 115-122 |
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| Authors: | LI JIE CHU Yan-Shuo CHENG Liang WANG Ya-Dong KONG Lei-Lei |
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| Affiliation: | School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China,School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China,School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China,School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China and School of Computer Science and Technology, Heilongjiang Institute of Technology, Harbin 150050, China |
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| Abstract: | Disease similarity studies for understanding the pathogenesis of complex diseases, diagnosis, prognosis and drug development are important. Recently, researchers constructed Disease Ontology disease (DO) by integrating a variety of disease terms, which builds up the foundation of disease similarity measurement based on DO. We summary disease similarity calculation methods based on DO-related information in this paper and discuss the issues and challenges in disease similarity measurement, offer helpful reference for further research. |
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| Keywords: | disease ontology disease similarity |
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