用ProHarMeD进行蛋白质基因元研究协调,机型化和药物重定位候选预测
Klaudia Adamowicz1, Lis Arend1, Andreas Maier1
1Institute for Computational Systems Biology, University of Hamburg, Hamburg, 22607, Germany.
NPJ systems biology and applications
|October 10, 2023
概括
ProHarMeD协调了多样化的蛋白质组学数据,使生物标志物发现和药物重新使用成为可能. 该工具整合了不同生物体和测试的研究,揭示了疾病机制和潜在的治疗候选者.
科学领域:
- 蛋白质组学是指蛋白质组学.
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 蛋白质组学技术对于识别生物标志物和疾病机制至关重要.
- 目前公开的蛋白质组学数据在研究中分散,阻碍了整合和分析.
- 非协调的标识符和各种实验系统阻碍了元分析和数据整合.
研究的目的:
- 介绍ProHarMeD,这是一个协调和比较多项研究蛋白质组学数据的工具.
- 为了促进疾病机制的提取,并确定药物重用候选人.
- 为无数据集成提供一个用户友好的平台 (web,Python,R).
主要方法:
- ProHarMeD在蛋白质和基因水平之间,以及通过ortolog映射在生物体之间执行ID和名称转换.
- 该工具生成了ID转换的详细日志,并识别了跨研究的共享ID.
- 它通过交互式可视化自动提出疾病机制和药物重定向候选人.
主要成果:
- 使用ProHarMeD的ID协调在骨再生数据集中将研究之间的共享基因增加了50%.
- 确定了潜在的疾病机制,以及五种药物标和20种药物重新定位候选药物.
- 一些已确定的候选药物,包括Fondaparinux,已证明对骨再生产生影响.
结论:
- ProHarMeD能够有效地协调多中心蛋白质组学数据,用于元分析.
- 该工具有助于评估ID转换成功,并促进疾病机制挖掘.
- ProHarMeD弥合了蛋白质组学,疾病机制发现和药物重新利用之间的差距.
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