| 生物统计及生物信息学前沿-Frontiers of Biostatistics and Bioinf |
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2020-06-21 00:00:00 |
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生物统计及生物信息学前沿-Frontiers of Biostatistics and Bioinf 目录
Preface to the USTC Alumni's SeriesFrom the Editors Shuangge Ma & Yuedong WangPreface Shaw-Hwa LoSection I Statistical GeneticsLinkage Analysis with Mixed Sample of Affected Full and Half Sib Pairs in the Presence of Uncertain Relationship Wenquan Cui, Hong Zhang, Yaning ]Pang, Zhaohai LiSequential Importance Sampling with Resampling in Molecular Population Genetics Yuguo ChenMultiple-trait Quantitative Trait Loci Mapping Using Stochastic Search Vari- able Selection Nan LinSection II Statistical Analysis of Microarray DataStatistical Analysis of Microarray Time Course Gene Expression Data with Functional Hierarchical Models Fangxin HongA Nonparametric Method for the Conservative Estimation of the Proportion of True Null Hypotheses Yinglei LaiPartial Consistent Normalization Methods of Microarray Data Heng PengVariance Estimation for Gene-expression Microarray Data Tiejun Tong, Yuedong WangSection III Computational BiologyA Study of Protein Subcellular Localization Prediction Huanqing Feng, Wenlong Xu, Xianghua Zhang, Ao Li, Dan Xie, Minghui WangComputational Methods for Biomolecular Sequence Comparison Kun-Mao Chao, Tao JiangStatistical Learning on a Complex Metabolomic Dataset Xiaodong Lin, Susan J. Siramonsy, Chris Beecher, Young Truong, S. Stanley YoungA Flexible Statistical Model for Chromatin Sequences Ji-Ping Wang, Liqun XiSection IV General MethodologySome Advances in Finite Mixture Models Jiahua ChenSmoothing Spline ANOVA with Heterogeneous Variances and Application to EEG Data Wensheng Guo, Ming DaiKernel Estimation in Longitudinal Data with Outcome-related Observation Times Donglin Zeng, Daohai YuA Computable Bound for the Geometric Convergence Rate of the Lasso Gibbs Sampler Hui ZouBrief Introduction of Authors
生物统计及生物信息学前沿-Frontiers of Biostatistics and Bioinf 节选
作为现代科学的一个重要分支，生物统计和生物信息学运用统计、数学和计算机科学的方法研究生物及医学问题。在《生物统计及生物信息学前沿(英文版)》中，收录了15篇文章介绍生物统计和生物信息学中统计方法的*新进展。由于篇幅有限，着重介绍了高维数据分析方法及其应用。和统计学的其他分支相比，高维数据分析方法及其应用还处在相对初级阶段，希望《生物统计及生物信息学前沿(英文版)》的出版能够推动此方向的研究。
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http://book.00-edu.com/tushu/sh1/202007/2623202.html |
