An Approach for Detecting Missed Tissue Proteins in Autoimmune Diseases

Rasha Elnemr, M. Rafea, Passent El-Kafrawy
{"title":"An Approach for Detecting Missed Tissue Proteins in Autoimmune Diseases","authors":"Rasha Elnemr, M. Rafea, Passent El-Kafrawy","doi":"10.1109/LT58159.2023.10092296","DOIUrl":null,"url":null,"abstract":"Autoimmune disease is a pathologic condition resulting from an induced error in the immune system leading to an autoimmune response with organ dysfunction or tissue damage. The discovery of autoantibodies in the blood is essential in the diagnosis of these diseases. Notice that the antibodies may not be the essential reason for the disease. It should be remarked that auto-antibodies are commonly found in all immunologically competent people and can increase during disease, infection, or injury. In some cases, autoantibodies can be the result, not the reason, of the disorder process. The existence of autoantibody responses has major significance in the diagnosis and prognosis of several autoimmune disorders.The goal of this work is to detect the set of missed tissue proteins that can be used in the diagnosis and treatment of a specific autoimmune disease. A hypothetical EDAS is generated. Ten thousand records are randomly created based on the mathematical model. The developed algorithm for missed tissue protein discovery is described. The presented tool can be used to diagnose autoimmune diseases in clinical laboratories.","PeriodicalId":142898,"journal":{"name":"2023 20th Learning and Technology Conference (L&T)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 20th Learning and Technology Conference (L&T)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LT58159.2023.10092296","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Autoimmune disease is a pathologic condition resulting from an induced error in the immune system leading to an autoimmune response with organ dysfunction or tissue damage. The discovery of autoantibodies in the blood is essential in the diagnosis of these diseases. Notice that the antibodies may not be the essential reason for the disease. It should be remarked that auto-antibodies are commonly found in all immunologically competent people and can increase during disease, infection, or injury. In some cases, autoantibodies can be the result, not the reason, of the disorder process. The existence of autoantibody responses has major significance in the diagnosis and prognosis of several autoimmune disorders.The goal of this work is to detect the set of missed tissue proteins that can be used in the diagnosis and treatment of a specific autoimmune disease. A hypothetical EDAS is generated. Ten thousand records are randomly created based on the mathematical model. The developed algorithm for missed tissue protein discovery is described. The presented tool can be used to diagnose autoimmune diseases in clinical laboratories.
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
一种检测自身免疫性疾病组织蛋白缺失的方法
自身免疫性疾病是一种由免疫系统诱导错误导致自身免疫反应与器官功能障碍或组织损伤引起的病理状态。在血液中发现自身抗体对诊断这些疾病至关重要。注意,抗体可能不是疾病的根本原因。值得注意的是,自身抗体常见于所有免疫功能正常的人,并且在疾病、感染或损伤期间会增加。在某些情况下,自身抗体可能是疾病过程的结果,而不是原因。自身抗体反应的存在对多种自身免疫性疾病的诊断和预后具有重要意义。这项工作的目的是检测一组缺失的组织蛋白,这些蛋白可用于诊断和治疗特定的自身免疫性疾病。生成一个假设的EDAS。10000条记录是根据数学模型随机创建的。描述了开发的缺失组织蛋白发现算法。提出的工具可用于诊断自身免疫性疾病在临床实验室。
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
A proposed Array of Quadrifilar Helix Antenna for CubeSat applications Detection of Hydrogen Leakage Using Different Machine Learning Techniques The Future Metavertainment Application development Blockchain in Healthcare for Achieving Patients’ Privacy Predicting COVID-19 Mortalities for Patients with Special Health Conditions Using an Agent-Based Model
×
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:481959085
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