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<\/p>\n
\u4ee3\u8868\u4f5c\uff1a
\n1. Yang Y*, Fang Q*. Prediction of glycopeptide fragment mass spectra by deep learning. Nature Communications, 2024, 15: 2448.
\n2. Wang J#, Huang Y#, Lu F, Xu Q, Yang Z, Jiang Y, Shi S, Pan J, Yang Y*, Fang Q*. Benchmarking informatics workflows for data-independent acquisition single-cell proteomics. Nature Communications, 2025, 16: 10276.
\n3. Yang Y#, Yan G, Wu M, Yang P, Cao W#*, Qiao L*. GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control. Nature Communications, 2021, 12: 6073.
\n4. Yang Y#, Liu X#, Shen C, Lin Y, Yang P, Qiao L*. In silico spectral libraries by deep learning facilitate data-independent acquisition proteomics. Nature Communications, 2020, 11: 146.
\n5. Yang Y#, Zhao D#, Luo J#, Lin L, Lin Y, Shan B*, Chen H*, Qiao L*. Quantitative site-specific glycoproteomics reveals glyco-signatures for breast cancer diagnosis. Analytical Chemistry, 2025, 97(1): 114\u2013121.<\/p>","protected":false},"featured_media":1419,"template":"","member_cat":[],"class_list":["post-1471","member","type-member","status-publish","has-post-thumbnail","hentry"],"acf":[],"_links":{"self":[{"href":"http:\/\/cnhupo.org.cn\/zh\/wp-json\/wp\/v2\/member\/1471","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/cnhupo.org.cn\/zh\/wp-json\/wp\/v2\/member"}],"about":[{"href":"http:\/\/cnhupo.org.cn\/zh\/wp-json\/wp\/v2\/types\/member"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/cnhupo.org.cn\/zh\/wp-json\/wp\/v2\/media\/1419"}],"wp:attachment":[{"href":"http:\/\/cnhupo.org.cn\/zh\/wp-json\/wp\/v2\/media?parent=1471"}],"wp:term":[{"taxonomy":"member_cat","embeddable":true,"href":"http:\/\/cnhupo.org.cn\/zh\/wp-json\/wp\/v2\/member_cat?post=1471"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}