scholarly journals cDNA expression array reveals heterogeneous gene expression profiles in three glioblastoma cell lines

Oncogene ◽  
1999 ◽  
Vol 18 (17) ◽  
pp. 2711-2717 ◽  
Author(s):  
Chang Hun Rhee ◽  
Kenneth Hess ◽  
James Jabbur ◽  
Maribelis Ruiz ◽  
Yu Yang ◽  
...  
Endocrinology ◽  
2000 ◽  
Vol 141 (12) ◽  
pp. 4805-4808 ◽  
Author(s):  
Didier Goidin ◽  
Laurent Kappeler ◽  
Jacques Perrot ◽  
Jacques Epelbaum ◽  
Danielle Gourdji

Oncogene ◽  
2002 ◽  
Vol 21 (42) ◽  
pp. 6549-6556 ◽  
Author(s):  
Jiafu Ji ◽  
Xin Chen ◽  
Suet Yi Leung ◽  
Jen-Tsan A Chi ◽  
Kent Man Chu ◽  
...  

2001 ◽  
Vol 18 (1) ◽  
pp. 13-21 ◽  
Author(s):  
Atsushi Sasaki ◽  
Shogo Ishiuchi ◽  
Tsugiyasu Kanda ◽  
Masatoshi Hasegawa ◽  
Yoichi Nakazato

2006 ◽  
Vol 2 ◽  
pp. S552-S552
Author(s):  
Boe-Hyun Kim ◽  
Jae-Il Kim ◽  
Eun-Kyoung Choi ◽  
Richard I. Carp ◽  
Yong-Sun Kim

Cells ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 675 ◽  
Author(s):  
Xia ◽  
Liu ◽  
Zhang ◽  
Guo

High-throughput technologies generate a tremendous amount of expression data on mRNA, miRNA and protein levels. Mining and visualizing the large amount of expression data requires sophisticated computational skills. An easy to use and user-friendly web-server for the visualization of gene expression profiles could greatly facilitate data exploration and hypothesis generation for biologists. Here, we curated and normalized the gene expression data on mRNA, miRNA and protein levels in 23315, 9009 and 9244 samples, respectively, from 40 tissues (The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GETx)) and 1594 cell lines (Cancer Cell Line Encyclopedia (CCLE) and MD Anderson Cell Lines Project (MCLP)). Then, we constructed the Gene Expression Display Server (GEDS), a web-based tool for quantification, comparison and visualization of gene expression data. GEDS integrates multiscale expression data and provides multiple types of figures and tables to satisfy several kinds of user requirements. The comprehensive expression profiles plotted in the one-stop GEDS platform greatly facilitate experimental biologists utilizing big data for better experimental design and analysis. GEDS is freely available on http://bioinfo.life.hust.edu.cn/web/GEDS/.


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