Name
Affiliation
Papers
LEMING SHI
Division of Systems Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA
16
Collaborators
Citations 
PageRank 
96
408
23.69
Referers 
Referees 
References 
941
328
95
Search Limit
100941
Title
Citations
PageRank
Year
Selecting a single model or combining multiple models for microarray-based classifier development?--a comparative analysis based on large and diverse datasets generated from the MAQC-II project.140.402011
Microarray platform consistency is revealed by biologically functional analysis of gene expression profiles.200.512009
Assessing batch effects of genotype calling algorithm BRLMM for the Affymetrix GeneChip Human Mapping 500 K array set using 270 HapMap samples.330.702008
The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies.102.012008
Very Important Pool (VIP) genes--an application for microarray-based molecular signatures.320.492008
Gene expression profiles distinguish the carcinogenic effects of aristolochic acid in target (kidney) and non-target (liver) tissues in rats.281.232006
Improvement in the reproducibility and accuracy of DNA microarray quantification by optimizing hybridization conditions.300.622006
Analysis of gene expression changes in relation to toxicity and tumorigenesis in the livers of Big Blue transgenic rats fed comfrey (Symphytum officinale).260.892006
Cross-platform comparability of microarray technology: intra-platform consistency and appropriate data analysis procedures are essential.594.012005
Bioinformatics approaches for cross-species liver cancer analysis based on microarray gene expression profiling.391.532005
Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS).80.932005
A microarray study of MPP+-treated PC12 Cells: Mechanisms of toxicity (MOT) analysis using bioinformatics tools.290.562005
Microarray scanner calibration curves: characteristics and implications.392.962005
QSAR Models Using a Large Diverse Set of Estrogens.151.642001
Mining and Visualizing Large Anticancer Drug Discovery Databases.102.232000
Mining the NCI Anticancer Drug Discovery Databases: Genetic Function Approximation for the QSAR Study of Anticancer Ellipticine Analogues.162.991998