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BACKGROUND Development of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. The accumulated experiment evidence supports the assumption that genes express and perform their functions in modular fashions in cells. Therefore, there is an open space for(More)
MOTIVATION According to current consistency metrics such as percentage of overlapping genes (POG), lists of differentially expressed genes (DEGs) detected from different microarray studies for a complex disease are often highly inconsistent. This irreproducibility problem also exists in other high-throughput post-genomic areas such as proteomics and(More)
  • Stephanos Pavlides, Aristotelis Tsirigos, Iset Vera, Neal Flomenberg, Philippe G. Frank, Mathew C. Casimiro +6 others
  • 2010
Caveolin-1 (-/-) null stromal cells are a novel genetic model for cancer-associated fibroblasts and myofibroblasts. Here, we used an unbiased informatics analysis of transcriptional gene profiling to show that Cav-1 (-/-) bone-marrow derived stromal cells bear a striking resemblance to the activated tumor stroma of human breast cancers. More specifically,(More)
Decreased expression of specific microRNAs (miRNAs) occurs in human tumors, which suggests a function for miRNAs in tumor suppression. Herein, levels of the miR-17-5p/miR-20a miRNA cluster were inversely correlated to cyclin D1 abundance in human breast tumors and cell lines. MiR-17/20 suppressed breast cancer cell proliferation and tumor colony formation(More)
  • Maria Genander, Michael M. Halford, Nan-Jie Xu, Malin Eriksson, Zuoren Yu, Zhaozhu Qiu +13 others
  • 2009
Signaling proteins driving the proliferation of stem and progenitor cells are often encoded by proto-oncogenes. EphB receptors represent a rare exception; they promote cell proliferation in the intestinal epithelium and function as tumor suppressors by controlling cell migration and inhibiting invasive growth. We show that cell migration and proliferation(More)
MOTIVATION Microarrays datasets frequently contain a large number of missing values (MVs), which need to be estimated and replaced for subsequent data mining. The focus of the paper is to study the effects of different MV treatments for cDNA microarray data on disease classification analysis. RESULTS By analyzing five datasets, we demonstrate that among(More)
  • Luke Gaughan, Jacqueline Stockley, Nan Wang, Stuart R. C. McCracken, Achim Treumann, Kelly Armstrong +6 others
  • 2011
The androgen receptor (AR) is a member of the nuclear hormone receptor family of transcription factors that plays a critical role in regulating expression of genes involved in prostate development and transformation. Upon hormone binding, the AR associates with numerous co-regulator proteins that regulate the activation status of target genes via flux to(More)
Determining protein functions is an important task in the post-genomic era. Most of the current methods work on some large-sized functional classes selected from functional categorization systems prior to the prediction processes. GESTs, a prediction approach previously proposed by us, is based on gene expression similarity and taxonomy similarity of the(More)
One of the key obstacles in making learning protocols realistic in applications is the need to supervise them, a costly process that often requires hiring domain experts. We consider the framework to use the world knowledge as indirect supervision. World knowledge is general-purpose knowledge, which is not designed for any specific domain. Then the key(More)