Genetic information for chronic disease prediction

M. Grasso, Darshana Dalvi, Soma Das, Matthew Gately, Vlad Korolev, Y. Yesha
{"title":"Genetic information for chronic disease prediction","authors":"M. Grasso, Darshana Dalvi, Soma Das, Matthew Gately, Vlad Korolev, Y. Yesha","doi":"10.1109/BIBMW.2011.6112535","DOIUrl":null,"url":null,"abstract":"Type 2 diabetes and coronary artery disease are commonly occurring polygenic diseases, which are responsible for significant morbidity and mortality. The identification of people at risk for these conditions has historically been based on clinical factors alone. Advances in genetics have raised the hope that genetic testing may aid in disease prediction, treatment, and prevention. Although intuitive, the addition of genetic information to increase the accuracy of disease prediction remains an unproven hypothesis. We present an overview of genetic issues involved in polygenic diseases, and summarize ongoing efforts to use this information for disease prediction.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"53 1","pages":"997-997"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBMW.2011.6112535","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Type 2 diabetes and coronary artery disease are commonly occurring polygenic diseases, which are responsible for significant morbidity and mortality. The identification of people at risk for these conditions has historically been based on clinical factors alone. Advances in genetics have raised the hope that genetic testing may aid in disease prediction, treatment, and prevention. Although intuitive, the addition of genetic information to increase the accuracy of disease prediction remains an unproven hypothesis. We present an overview of genetic issues involved in polygenic diseases, and summarize ongoing efforts to use this information for disease prediction.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
慢性病预测的遗传信息
2型糖尿病和冠状动脉疾病是常见的多基因疾病,发病率和死亡率都很高。历史上,对这些疾病高危人群的识别仅基于临床因素。遗传学的进步带来了基因检测有助于疾病预测、治疗和预防的希望。虽然是直观的,但增加遗传信息以提高疾病预测的准确性仍然是一个未经证实的假设。我们概述了涉及多基因疾病的遗传问题,并总结了利用这些信息进行疾病预测的持续努力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Evolution of protein architectures inferred from phylogenomic analysis of CATH Hierarchical modeling of alternative exon usage associations with survival 3D point cloud sensors for low-cost medical in-situ visualization Bayesian Classifiers for Chemical Toxicity Prediction Normal mode analysis of protein structure dynamics based on residue contact energy
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1