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| 1 | The HuangZaoSi Maize Genome Provides Insights into Genomic Variation and Improvement History of Maize显示文摘Maize is a globally important crop that was a classic model plant for genetic studies. Here, we report a 2.2 Gb draft genome sequence of an elite maize line, HuangZaoSi (HZS). Hybrids bred from HZS-improved lines (HILs) are planted in more than 60% of maize fields in China. Proteome clustering of six completed sequeneed maize genomes show that 638 proteins fall into 264 HZS-specific gene families with the majority of contributions from tandem duplication events. Resequencing and comparative analysis of 40 HZSrelated lines reveals the breeding history of HILs. More than 60% of identified selective sweeps were clustered in identity.by.descent conserved regions, and yield-related genes/QTLs were enriched in HZS characteristic selected regions. Furthermore, we dem on strated that HZS-specific family genes were not uniformly distributed in the genome but enriched in improvement/function.related genomic regions. This study provides an important and novel resource for maize genome research and expands our knowledge on the breadth of genomic variation and improvement history of maize. | Chunhui Li Wei Song Yingfeng Luo Shenghan Gao Ruyang Zhang Zi Shi Xiaqing Wang Ronghuan Wang Fengge Wang Jidong Wang Yanxin Zhao Aiguo Su Shuai Wang Xin Li Meijie Luo Shuaishuai Wang Yunxia Zhang Jianrong Ge Xinyu Tan Ye Yuan Xiaochun Bi Hang He Jianbing Yan Yuandong Wang Songnian Hu Jiuran Zhao | 2019 | Molecular Plant2019，12，3： | 15 |
| 2 | Formation of Oxygen Vacancies on the {010} Facets of BiOCl and Visible Light Activity for Degradation of Ciprofloxacin显示文摘 | ZENG Xiaoxing GONG Xiaofeng WAN Yiqun HE Ruyang XU Zhaodi | 2018 | Chemical Research in Chinese Universities2018，34，5： | 1 |
| 3 | Variable Importance Measure System Based on Advanced Random Forest显示文摘The variable importance measure(VIM)can be implemented to rank or select important variables,which can effectively reduce the variable dimension and shorten the computational time.Random forest(RF)is an ensemble learning method by constructing multiple decision trees.In order to improve the prediction accuracy of random forest,advanced random forest is presented by using Kriging models as the models of leaf nodes in all the decision trees.Referring to the Mean Decrease Accuracy(MDA)index based on Out-of-Bag(OOB)data,the single variable,group variables and correlated variables importance measures are proposed to establish a complete VIM system on the basis of advanced random forest.The link of MDA and variance-based sensitivity total index is explored,and then the corresponding relationship of proposed VIM indices and variance-based global sensitivity indices are constructed,which gives a novel way to solve variance-based global sensitivity.Finally,several numerical and engineering examples are given to verify the effectiveness of proposed VIM system and the validity of the established relationship. | Shufang Song Ruyang He Zhaoyin Shi Weiya Zhang | 2021 | Computer Modeling in Engineering & Sciences2021，，7： | 0 |
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