药物和疾病啥关系 ？ 李智恒.

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1 药物和疾病啥关系 ？ 李智恒

2 任务： BioCreative V Chemical-induced diseases relation extraction (CID) 1. V CDR Task: Identifying Chemical-induced Disease Relations in Biomedical Text 2. RELigator: Chemical-disease relation extraction using prior knowledge and textual information

3 任务介绍 BioCreative V Chemical-induced diseases relation extraction (CID)

4 UTH-CCB@BioCreative V CDR Task
sentence level Cs CID pair located in the same sentence CID abstract level  CD all candidate CID pairs Cs classifier : Context words with position Knowledgebase features Others

5 Cs features 1 Context words with position: eg:
C_D induced D_D in a D_D child. target entities: C_D , D_D009422 unigram and bigram words before, between and after target entities other entities between  entity type C_D induced D_disease in a D_D child.

6 Cs features 2 Knowledgebase features:
all relations of the chemical and disease pair in the CTD, MEDI, SIDER MeSH® tree structures of entities

7 CTD Comparative Toxicgenomics Database（ http://ctdbase.org/ ）
研究环境化学对人体健康的影响

8 CTD 研究实体： chemical/drugs genes/proteins disease taxa（分类群）
phenotypes（基因型和环境相互作用下的有机体的样子，显型） 人工标注： chemical–gene/protein interactions chemical–disease relationships gene–disease relationships chemical–phenotype relationships

9 CTD 数据分类： Chemical , Disease , Genes
Chemical–Gene/Protein Interactions Gene–Disease Associations Chemical–Disease Associations Gene–Gene Interactions References Organisms Gene Ontology Pathways Exposures

10 CTD Chemical–Disease Associations 下载文件： CTD chemical disease.xml.gz
therapeutic（治疗剂）或marker/mechanism（机制原理） 或 缺省

11 Cs features 2 Knowledgebase features:
all relations of the chemical and disease pair in the CTD, MEDI, SIDER MeSH® tree structures of entities

12 MEDI MEDI--an Ensemble MEDication Indication Resource
（ ） 电子病历中提取得到的药物指示资源

13 Cs features 2 Knowledgebase features:
all relations of the chemical and disease pair in the CTD, MEDI, SIDER MeSH® tree structures of entities

14 SIDER Side Effect Resource（http://sideeffects.embl.de/）
销售药品和其他记录中的不良反应 从公开文档和包装说明书中抽取的信息 可用信息：副作用频率、药物副作用分类、 更多的信息链接（eg: drug-target relations）

15 SIDER

16 Cs features 2 Knowledgebase features:
all relations of the chemical and disease pair in the CTD, MEDI, SIDER MeSH® tree structures of entities

17 MeSH® tree structures 可以根据参考是找到比给定标题更具体、更广泛的标题 四肢 截肢残端 下肢 臀部 脚 脚踝
前脚掌，人类 跖骨 脚趾 大拇趾

18 Cs features 3 Others Mentions and normalized values of entities
Core chemicals: highest frequency or occurred in the title +1： 所有包含CID 关系对的句子 CID-SA —— -1 ： 不包含CID 关系对的句子 +1 ： 人工标注，确实含有关系的句子 CID-SM—— -1 ： 人工标注，不含关系，但包含CID对的句子

19 CD classifier （2），（3） of Cs ( Knowledge features & core chemical )
Number of sentences between entities Trigger words For all CID pairs Cs+CD  predictions 若抽取结果为空，则核心化合物连接的CID对加入最终结果集

20 Results Training set + development set final models 自动标注优于人工标注结果

21 References CTD： The Comparative Toxicogenomics Database's 10th year anniversary: update 2015. MEDI： Development and evaluation of an ensemble resource linking medications to their indications. （2013） SIDER: A side effect resource to capture phenotypic effects of drugs.(2010)

22 RELigator RELigator: Chemical-disease relation extraction using prior knowledge and textual information Relation extraction: All co-occurrence pairs Cross the title-abstract border Features: Knowledge-based features Statistical features NLP features

23 Knowledge-based features
BRAIN : a graph database UMLS 中几乎所有的实体的相关关系 （来自结构化数据库&Medline文章） Entity1 connection Entity2 （每个connection标有来源，不同来源标有不同权重） （每个connection关联一系列 关系或预测） BRAIN提供用户编程接口，可用于查询两个给定实体的关系路径(path) 关系路径：直接/间接，每个path有志新分数， 用于衡量2个实体之间的连接紧密程度

24 Statistical features chemical , disease , chemical-disease pair 文档中出现频次 chemical 和 disease间的：1. 最少句子间隔 2.最少单词间隔 chemical 和 disease是否出现在title中，或者二者均出现在title中

25 NLP features Stanford CoreNLP parser 产生句子的依存树
Governing verb：分析树中某节点上升到根的过程中遇到的第一个动词 Semantic role：实体的语义角色由分析树中的governing verb 反映 对于最近的chemical和disease: Relating word （担任） Governing verb of Relating word （宣布） Chemical是否在disease前 是否有chemical-disease pair在低一级的分析树中 所有governing verb & 出现频次

26 Machine learning SVM分类 Radial basis function Grid search
Ten-fold cross-validation

27 References BRAIN： Bio-IT World. Big BRAIN: Finding Connections in the Literature Flood with Euretos BRAIN[ Internet]. Available from: Euretos[Internet]. Available from:

28 Sequence Modeling： Recurrent and Recursive Nets
张建海

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