<HashMap><database>iProX</database><scores/><additional><omics_type>Proteomics</omics_type><submitter>Ming Dong</submitter><species>Homo Sapiens</species><full_dataset_link>http://www.iprox.org/page/project.html?id=IPX0017982000</full_dataset_link><submitter_email>dong_ming@gzlab.ac.cn</submitter_email><submitter_affiliation>Guangzhou National Laboratory</submitter_affiliation><sample_protocol></sample_protocol><repository>iProX</repository><data_protocol></data_protocol></additional><is_claimable>false</is_claimable><name>An Sequential Workflow for Small Extracellular Vesicle Biomarkers Discovery and Validation: Coupling Machine Learning-Based Mining with High-Efficiency Microfluidic Isolation</name><description>By coupling machine learning mining with microfluidic isolation, this stepwise workflow provides a robust, standardized framework for the discovery and rapid validation of exosomal biomarkers. This approach offers a scalable solution for cancer diagnostics and supports the development of precision diagnostic tools</description><dates><publication>Mon Jun 29 00:00:00 BST 2026</publication></dates><accession>PXD080311</accession><cross_references><TAXONOMY>9606</TAXONOMY></cross_references></HashMap>