Group SCAD regression analysis for microarray time course gene expression data

By Lifeng Wang, Guang Chen, Hongzhe Li. Bioinform., 2007

297 citations recorded by the source corpus.

Subfields: Molecular Biology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/07c4e5120d9d4356f5d39371a689d20425a9c6f7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Heng Peng
2. Tao Hu
3. Heng Lian
4. Chenlei Leng
5. Jian Huang
6. Toshio Honda
7. Sunduz Keles
8. Ming-Yen Cheng

In Statistics and Probability

1. Heng Lian
2. Chenlei Leng
3. Jian Huang
4. Tao Hu
5. Yingcun Xia
6. Patrick Breheny
7. Ming-Yen Cheng
8. Heng Peng

Citations in the corpus

• A simple approach for varying-coefficient model selection (2009, methodology): “More recently, Wang et al. (2007) and Wang and Li (2007) proposed to use group SCAD method for varying-coefficient model selection.”
• Sparse partial least squares regression for simultaneous dimension reduction and variable selection (2010, methodology): “There are a total 21 experimentally confirmed cell cycle related tf s (Wang et al., 2007), and we report the number of confirmed tf s among the selected ones as a guideline for performance comparison of the methods.”
• ADAPTIVE SEMI-VARYING COEFFICIENT MODEL SELECTION (2012, methodology): “Wang, Chen, and Li (2007) and Wang, Li, and Huang (2008) used the SCAD method to remove variables from the varying-coefficient models.”
• Nonparametric independence screening and structure identification for ultra-high dimensional longitudinal data (2013, methodology): “Using the same subset of the original data as [29], we included totally p = 96 TFs as covariates in the following analysis.”
• Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors (2012, background): “2), as has been proposed in Wang et al. (2007) and discussed in Huang et al.”
• Shrinkage estimation and selection for multiple functional regression (2011, methodology): “ article we use functional principle component analysis (PCA)-based estimation method (Cardot et al., 1999; Hall and Horowitz, 2007) combined with group SCAD (this terminology seems to first appear in Wang et al. (2007) for varying coefficients variable selection) which represents a new application of ”