T
Tianwei Yu
Researcher at Emory University
Publications - 166
Citations - 6701
Tianwei Yu is an academic researcher from Emory University. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 38, co-authored 132 publications receiving 5577 citations. Previous affiliations of Tianwei Yu include The Chinese University of Hong Kong & University of Illinois at Chicago.
Papers
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Journal ArticleDOI
K-Profiles: A Nonlinear Clustering Method for Pattern Detection in High Dimensional Data.
TL;DR: The nonlinear K-profiles clustering method is designed, which can be seen as the nonlinear counterpart of the K-means clustering algorithm, and has a built-in statistical testing procedure that ensures genes not belonging to any cluster do not impact the estimation of cluster profiles.
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Salivary proteomic and genomic biomarkers for primary sjögren's syndrome
Shen Hu,Jianghua Wang,Jiska Meijer,Sonya Ieong,Yongming Xie,Tianwei Yu,Hui Zhou,Sharon Henry,Arjan Vissink,J. Pijpe,Cees G. M. Kallenberg,David Elashoff,Joseph A. Loo,David T.W. Wong +13 more
TL;DR: It is found that WS contains more informative proteins, peptides, and mRNA, as compared with gland-specific saliva, that can be used in generating candidate biomarkers for the detection of primary SS.
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Transcriptomic dissection of tongue squamous cell carcinoma
Hui Ye,Tianwei Yu,Stéphane Temam,Stéphane Temam,Barry L. Ziober,Jianguang Wang,Joel L. Schwartz,Li Mao,David T.W. Wong,Xiaofeng Zhou,Xiaofeng Zhou +10 more
TL;DR: This study provided a transcriptomic signature for OTSCC that may lead to a diagnosis or screen tool and provide the foundation for further functional validation of these specific candidate genes for O TSCC.
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apLCMS—adaptive processing of high-resolution LC/MS data
TL;DR: A set of algorithms for the processing of high-resolution LC/MS data, including the adaptive tolerance level searching rather than hard cutoff or binning, the use of non-parametric methods to fine-tune intensity grouping, and the model-based estimation of peak intensities for absolute quantification are presented.
Journal ArticleDOI
xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data
Karan Uppal,Karan Uppal,Quinlyn A. Soltow,Fred Strobel,W. Stephen Pittard,Kim M. Gernert,Tianwei Yu,Dean P. Jones +7 more
TL;DR: The xMSanalyzer program was designed to integrate with existing packages such as apLCMS and XCMS, but the framework can also be used to enhance data extraction for other LC/MS data software.