Tianwei Yu,Yize Zhao,Shihao Shen
Tianwei Yu
Joint analyses of high-throughput datasets generate the need to assess the association between two long lists of p-values. In such p-value lists, the vast majority of the features are insignificant. Ideally contributions of features that ar...
Predicting Simulation Parameters of Biological Systems Using a Gaussian Process Model [0.03%]
基于高斯过程模型的生物系统模拟参数预测方法研究
Xiangxin Zhu,Max Welling,Fang Jin et al.
Xiangxin Zhu et al.
Finding optimal parameters for simulating biological systems is usually a very difficult and expensive task in systems biology. Brute force searching is infeasible in practice because of the huge (often infinite) search space. In this artic...
Tong Tong Wu,Yichao Wu
Tong Tong Wu
The novel supervised learning method of vertex discriminant analysis (VDA) has been demonstrated for its good performance in multicategory classification. The current paper explores an elaboration of VDA for nonlinear discrimination. By inc...
Ashin Mukherjee,Ji Zhu
Ashin Mukherjee
In multivariate linear regression, it is often assumed that the response matrix is intrinsically of lower rank. This could be because of the correlation structure among the prediction variables or the coefficient matrix being lower rank. To...
Ferit Akova,Murat Dundar,V Jo Davisson et al.
Ferit Akova et al.
Technologies for rapid detection of bacterial pathogens are crucial for securing the food supply. A light-scattering sensor recently developed for real-time identification of multiple colonies has shown great promise for distinguishing bact...
Sequential Support Vector Regression with Embedded Entropy for SNP Selection and Disease Classification [0.03%]
基于嵌入熵的顺序支持向量回归SNP选择及疾病分类方法
Yulan Liang,Arpad Kelemen
Yulan Liang
Comprehensive evaluation of common genetic variations through association of SNP structure with common diseases on the genome-wide scale is currently a hot area in human genome research. For less costly and faster diagnostics, advanced comp...
Controlling the False Discovery Rate for Feature Selection in High-resolution NMR Spectra [0.03%]
高分辨率NMR光谱特征选择中的假发现率控制
Seoung Bum Kim,Victoria C P Chen,Youngja Park et al.
Seoung Bum Kim et al.
Successful implementation of feature selection in nuclear magnetic resonance (NMR) spectra not only improves classification ability, but also simplifies the entire modeling process and, thus, reduces computational and analytical efforts. Pr...
Seo Young Park,Yufeng Liu,Dacheng Liu et al.
Seo Young Park et al.
Classification is a very useful statistical tool for information extraction. In particular, multicategory classification is commonly seen in various applications. Although binary classification problems are heavily studied, extensions to th...
Yongli Zhang,Xiaotong Shen
Yongli Zhang
For high-dimensional regression, the number of predictors may greatly exceed the sample size but only a small fraction of them are related to the response. Therefore, variable selection is inevitable, where consistent model selection is the...
Gene expression associations with the growth inhibitory effects of small molecules on live cells: specificity of effects and uniformity of mechanisms [0.03%]
小分子活细胞生长抑制作用与基因表达的相关性：效应的特异性和机制的一致性
Kerby Shedden,Yang Yang,Gus Rosania
Kerby Shedden
The NCI60 human tumor cell line screen is a public resource for studying selective and non-selective growth inhibition of small molecules against cancer cells. By coupling growth inhibition screening data with biological characterizations o...