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Yu-Ping Wang
Researcher at Tulane University
Publications - 367
Citations - 5304
Yu-Ping Wang is an academic researcher from Tulane University. The author has contributed to research in topics: Canonical correlation & Computer science. The author has an hindex of 31, co-authored 335 publications receiving 3911 citations. Previous affiliations of Yu-Ping Wang include Washington University in St. Louis & Shanghai University.
Papers
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Journal ArticleDOI
Comparative Studies of Copy Number Variation Detection Methods for Next-Generation Sequencing Technologies
TL;DR: This work compared six publicly available CNV detection methods: CNV-seq, FREEC, readDepth, CNVnator, SegSeq and event-wise testing and provides a comprehensive evaluation on the performances of the selected CNV Detection methods, which will help biological investigators choose the best possible method.
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A survey on U-shaped networks in medical image segmentations
Liangliang Liu,Liangliang Liu,Jianhong Cheng,Quan Quan,Fang-Xiang Wu,Yu-Ping Wang,Jianxin Wang +6 more
TL;DR: A comprehensive literature review of U-shaped networks applied to medical image segmentation tasks, focusing on the architectures, extended mechanisms and application areas in these studies.
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π Berry phase and Zeeman splitting of Weyl semimetal TaP
Jin Hu,Jinyu Liu,David Graf,S. M. A. Radmanesh,D. J. Adams,Alyssa Chuang,Yu-Ping Wang,Irinel Chiorescu,Jiang Wei,Leonard Spinu,Zhiqiang Mao +10 more
TL;DR: The determination of Berry phases of multiple Fermi pockets of Weyl semimetal TaP through high field quantum transport measurements is reported and the TaP single crystal has the signatures of a Weyl state, including light effective quasiparticle masses, ultrahigh carrier mobility, as well as negative longitudinal magnetoresistance.
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Correspondence between fMRI and SNP data by group sparse canonical correlation analysis
TL;DR: A group sparse canonical correlation analysis method (group sparse CCA) was developed to explore the correlation between these two datasets which are high dimensional-the number of SNPs/voxels is far greater than the number of samples.
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Multistage genome-wide association meta-analyses identified two new loci for bone mineral density.
Lei Zhang,Hyung Jin Choi,Karol Estrada,Paul Leo,Jian Li,Yu-Fang Pei,Yin-Ping Zhang,Yong Lin,Hui Shen,Yao Zhong Liu,Yong Jun Liu,Yingchun Zhao,Ji Gang Zhang,Qing Tian,Yu-Ping Wang,Yingying Han,Shu Ran,Rong Hai,Xue Zhen Zhu,Shuyan Wu,Han Yan,Xiao-Gang Liu,Tie-Lin Yang,Yan Guo,Feng Zhang,Yan Fang Guo,Yuan Chen,Xiang-Ding Chen,Li-Jun Tan,Li-Shu Zhang,Fei-Yan Deng,H.-W. Deng,Fernando Rivadeneira,Emma L. Duncan,Emma L. Duncan,Jong-Young Lee,Bok Ghee Han,Nam H. Cho,Geoffrey C. Nicholson,Eugene V. McCloskey,Richard Eastell,Richard L. Prince,Richard L. Prince,John A. Eisman,Graeme Jones,Ian R. Reid,Philip N. Sambrook,Elaine M. Dennison,Patrick Danoy,Laura M. Yerges-Armstrong,Elizabeth A. Streeten,Elizabeth A. Streeten,Tian Hu,Shuanglin Xiang,Christopher J. Papasian,Matthew A. Brown,Chan Soo Shin,André G. Uitterlinden,Hong-Wen Deng +58 more
TL;DR: A three-stage genome-wide association meta-analysis conducted in 27 061 study subjects independently confirm previously identified biological pathways underlying bone metabolism and contribute to the discovery of novel pathways, thus providing valuable insights into the intervention and treatment of osteoporosis.