{"title":"用于预测基因功能特性的文本信息","authors":"Oana Frunza, D. Inkpen","doi":"10.3115/1572306.1572334","DOIUrl":null,"url":null,"abstract":"This paper is focused on determining which proteins affect the activity of Aryl Hydrocarbon Receptor (AHR) system when learning a model that can accurately predict its activity when single genes are knocked out. Experiments with results are presented when models are trained on a single source of information: abstracts from Medline (http://medline.cos.com/) that talk about the genes involved in the experiments. The results suggest that AdaBoost classifier with a binary bag-of-words representation obtains significantly better results.","PeriodicalId":200974,"journal":{"name":"Workshop on Biomedical Natural Language Processing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Textual Information for Predicting Functional Properties of the Genes\",\"authors\":\"Oana Frunza, D. Inkpen\",\"doi\":\"10.3115/1572306.1572334\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper is focused on determining which proteins affect the activity of Aryl Hydrocarbon Receptor (AHR) system when learning a model that can accurately predict its activity when single genes are knocked out. Experiments with results are presented when models are trained on a single source of information: abstracts from Medline (http://medline.cos.com/) that talk about the genes involved in the experiments. The results suggest that AdaBoost classifier with a binary bag-of-words representation obtains significantly better results.\",\"PeriodicalId\":200974,\"journal\":{\"name\":\"Workshop on Biomedical Natural Language Processing\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Workshop on Biomedical Natural Language Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3115/1572306.1572334\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Biomedical Natural Language Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3115/1572306.1572334","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Textual Information for Predicting Functional Properties of the Genes
This paper is focused on determining which proteins affect the activity of Aryl Hydrocarbon Receptor (AHR) system when learning a model that can accurately predict its activity when single genes are knocked out. Experiments with results are presented when models are trained on a single source of information: abstracts from Medline (http://medline.cos.com/) that talk about the genes involved in the experiments. The results suggest that AdaBoost classifier with a binary bag-of-words representation obtains significantly better results.