Jian Huang
Zhejiang University
1596 Papers
7.2K Citations
Jian Huang is an academic researcher from Zhejiang University. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 97, co-authored 1189 publications. Previous affiliations of Jian Huang include Wuhan University of Technology & Chinese National Human Genome Center.
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Papers
Associations of residential green space with incident type 2 diabetes and the role of air pollution: A prospective analysis in UK Biobank.
TL;DR: Wang et al. as mentioned in this paper evaluated the longitudinal association between residential green space and incident type 2 diabetes, and further illustrate the role of air pollution in a prospective analysis in UK Biobank.
22
A robust two-way semi-linear model for normalization of cDNA microarray data
TL;DR: A robust semiparametric method in a two-way semi-linear model (TW-SLM) for normalization of cDNA microarray data that works at least as well as the LOWESS method and works better when the underlying assumptions for the LOWess method are not satisfied.
Microstructure and mechanical deformation behavior of selective laser melted Ti6Al4V ELI alloy porous structures
Cheng Chang,Jian Huang,Xingchen Yan,Xingchen Yan,Qing Li,Min Liu,Sihao Deng,Julien Gardan,Rodolphe Bolot,Mahdi Chemkhi,Hanlin Liao +10 more
TL;DR: In this paper, the compressive properties and deformation behavior of selective laser melted (SLM) Ti6Al4V ELI porous structures were studied using phase composition and microstructure characteristics, a number of fine acicular a′ martensite (93.3%) and a bit β phase (6.6%) can be detected in SLM porous structures.
22
Microstructure and mechanical properties of laser welded-brazed titanium/aluminum joints assisted by titanium mesh interlayer
TL;DR: Li et al. as discussed by the authors proposed a novel method of laser welding-brazing aluminum to titanium assisted by a titanium mesh interlayer to further improve load capacity of Ti/Al joints.
22
Incorporating higher-order representative features improves prediction in network-based cancer prognosis analysis.
TL;DR: This study introduces multiple ways of defining the representative features and effective thresholding regularized estimation approaches and provides convincing evidence that the higher-order representative features may have important implications for the prediction of cancer prognosis.