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Wei-Jun Qian

Researcher at Pacific Northwest National Laboratory

Publications -  255
Citations -  13288

Wei-Jun Qian is an academic researcher from Pacific Northwest National Laboratory. The author has contributed to research in topics: Proteomics & Proteome. The author has an hindex of 58, co-authored 220 publications receiving 11062 citations. Previous affiliations of Wei-Jun Qian include Centers for Disease Control and Prevention & Nanjing University.

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Human Plasma N-Glycoproteome Analysis by Immunoaffinity Subtraction, Hydrazide Chemistry, and Mass Spectrometry

TL;DR: An approach for broad analysis of human plasma N-glycoproteins using a combination of immunoaffinity subtraction and glycoprotein capture to reduce both the protein concentration range and the overall sample complexity is described.
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DAnTE: a statistical tool for quantitative analysis of -omics data

TL;DR: DAnTE features selected normalization methods, missing value imputation algorithms, peptide-to-protein rollup methods, an extensive array of plotting functions and a comprehensive hypothesis-testing scheme that can handle unbalanced data and random effects.
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Normalization Approaches for Removing Systematic Biases Associated with Mass Spectrometry and Label-Free Proteomics

TL;DR: Central tendency, linear regression, locally weighted regression, and quantile techniques were investigated for normalization of peptide abundance measurements obtained from high-throughput liquid chromatography-Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR MS).
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Nanodroplet processing platform for deep and quantitative proteome profiling of 10-100 mammalian cells.

TL;DR: A robotically controlled chip-based nanodroplet processing platform is established and its ability to profile the proteome from 10–100 mammalian cells is demonstrated, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.
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Advances and Challenges in Liquid Chromatography-Mass Spectrometry-based Proteomics Profiling for Clinical Applications

TL;DR: This review summarizes recent advances in LC-MS-based proteomics profiling and its applications in clinical proteomics as well as discuss the major challenges associated with implementing these technologies for more effective candidate biomarker discovery.