首页> Patterns (New York, N.Y.)> A privacy-preserving approach for cloud-based protein fold recognition.

A privacy-preserving approach for cloud-based protein fold recognition.

导出 LinkOut

翻译打印收藏纠错

第一作者： Ali Burak,Ünal

第一单位： Medical Data Privacy and Privacy Preserving Machine Learning (MDPPML), Department of Computer Science, University of Tübingen, 72076 Tübingen, Germany.;Institute for Bioinformatics and Medical Informatics (IBMI), Department of Computer Science, University of Tübingen, 72076 Tübingen, Germany.

作者： Ali Burak,Ünal ^[1] ; Nico,Pfeifer ^[2] ; Mete,Akgün ^[1]

作者单位： Medical Data Privacy and Privacy Preserving Machine Learning (MDPPML), Department of Computer Science, University of Tübingen, 72076 Tübingen, Germany.;Institute for Bioinformatics and Medical Informatics (IBMI), Department of Computer Science, University of Tübingen, 72076 Tübingen, Germany. ^[1] Methods in Medical Informatics, Department of Computer Science, University of Tübingen, 72076 Tübingen, Germany.;Institute for Bioinformatics and Medical Informatics (IBMI), Department of Computer Science, University of Tübingen, 72076 Tübingen, Germany. ^[2]

关键词 cloud-based machine learning data privacy machine learning as a service multi-party computation privacy preserving machine learning protein fold recognition recurrent kernel networks

DOI 10.1016/j.patter.2024.101023

PMID 39568647

发布时间 2024-11-22

翻译满意度评价：

准确一般字义偏差语意偏离译文作用小提交

浏览0

Patterns (New York, N.Y.)

2024年5卷9期

101023页

相似文献

中文期刊
外文期刊
学位论文
会议论文

浏览0

Patterns (New York, N.Y.)

2024年5卷9期

101023页

检索历史清除

A privacy-preserving approach for cloud-based protein fold recognition.

Patterns (New York, N.Y.)

相似文献

同项目论文

Patterns (New York, N.Y.)

相关期刊

参考文献：
指定格式：	NoteExpress EndNote RefWorks NoteFirst

检索历史 清除

A privacy-preserving approach for cloud-based protein fold recognition.

Patterns (New York, N.Y.)

相似文献

同项目论文

Patterns (New York, N.Y.)

相关期刊

检索历史清除