2008 |
12 | EE | Caiyan Li,
Hongzhe Li:
In Response to Comment on "Network-constrained regularization and variable selection for analysis of genomic data".
Bioinformatics 24(21): 2569 (2008) |
11 | EE | Caiyan Li,
Hongzhe Li:
Network-constrained regularization and variable selection for analysis of genomic data.
Bioinformatics 24(9): 1175-1182 (2008) |
2007 |
10 | EE | Lifeng Wang,
Guang Chen,
Hongzhe Li:
Group SCAD regression analysis for microarray time course gene expression data.
Bioinformatics 23(12): 1486-1494 (2007) |
9 | EE | Zhi Wei,
Hongzhe Li:
A Markov random field model for network-based analysis of genomic data.
Bioinformatics 23(12): 1537-1544 (2007) |
2005 |
8 | EE | Jiang Gui,
Hongzhe Li:
Threshold Gradient Descent Method for Censored Data Regression with Applications in Pharmacogenomics.
Pacific Symposium on Biocomputing 2005 |
7 | EE | Hongzhe Li,
Yihui Luan:
Boosting proportional hazards models using smoothing splines, with applications to high-dimensional microarray data.
Bioinformatics 21(10): 2403-2409 (2005) |
6 | EE | Jiang Gui,
Hongzhe Li:
Penalized Cox regression analysis in the high-dimensional and low-sample size settings, with applications to microarray gene expression data.
Bioinformatics 21(13): 3001-3008 (2005) |
2004 |
5 | EE | Hongzhe Li,
Jiang Gui:
Partial Cox regression analysis for high-dimensional microarray gene expression data.
ISMB/ECCB (Supplement of Bioinformatics) 2004: 208-215 |
4 | EE | Lexin Li,
Hongzhe Li:
Dimension reduction methods for microarrays with application to censored survival data.
Bioinformatics 20(18): 3406-3412 (2004) |
3 | EE | Yihui Luan,
Hongzhe Li:
Model-based methods for identifying periodically expressed genes based on time course microarray gene expression data.
Bioinformatics 20(3): 332-339 (2004) |
2003 |
2 | EE | Hongzhe Li,
Yihui Luan:
Kernel Cox Regression Models for Linking Gene Expression Profiles to Censored Survival Data.
Pacific Symposium on Biocomputing 2003: 65-76 |
1 | | Yihui Luan,
Hongzhe Li:
Clustering of time-course gene expression data using a mixed-effects model with B-splines.
Bioinformatics 19(4): 474-482 (2003) |