Hung-I Harry Chen

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MOTIVATION When identifying differentially expressed (DE) genes from high-throughput gene expression measurements, we would like to take both statistical significance (such as P-value) and biological relevance (such as fold change) into consideration. In gene set enrichment analysis (GSEA), a score that can combine fold change and P-value together is needed(More)
Increasing evidence suggests that chromosomal regions containing microRNAs are functionally important in cancers. Here, we show that genomic loci encoding miR-204 are frequently lost in multiple cancers, including ovarian cancers, pediatric renal tumors, and breast cancers. MiR-204 shows drastically reduced expression in several cancers and acts as a potent(More)
BACKGROUND microRNAs (miRNAs) have been implicated in the control of many biological processes and their deregulation has been associated with many cancers. In recent years, the cancer stem cell (CSC) concept has been applied to many cancers including pediatric. We hypothesized that a common signature of deregulated miRNAs in the CSCs fraction may explain(More)
MOTIVATION Genomic instability is one of the fundamental factors in tumorigenesis and tumor progression. Many studies have shown that copy-number abnormalities at the DNA level are important in the pathogenesis of cancer. Array comparative genomic hybridization (aCGH), developed based on expression microarray technology, can reveal the chromosomal(More)
BACKGROUND Circular Binary Segmentation (CBS) is a permutation-based algorithm for array Comparative Genomic Hybridization (aCGH) data analysis. CBS accurately segments data by detecting change-points using a maximal-t test; but extensive computational burden is involved for evaluating the significance of change-points using permutations. A recent(More)
RNA sequencing (RNA-seq) is a powerful tool for genome-wide expression profiling of biological samples with the advantage of high-throughput and high resolution. There are many existing algorithms nowadays for quantifying expression levels and detecting differential gene expression, but none of them takes the misaligned reads that are mapped to non-exonic(More)
The problem of large scale computational drug screening is considered in this paper. A new concept of Mode-of-Action (MoA) network, or MoNet, is introduced to model the relationship of therapeutic effectiveness between different drugs. A new algorithm for constructing Mode-of-Action groups and subsequently MoNet based on gene expression profile of drug(More)
The purpose of this study is to characterize the microRNA (miRNA) expression profiles of induced pluripotent stem (iPS) cells and retinal pigment epithelium (RPE) derived from induced pluripotent stem cells (iPS-RPE). MiRNAs have been demonstrated to play critical roles in both maintaining pluripotency and facilitating differentiation. Gene expression(More)
—Transcriptional regulation by transcription factors (TFs) and microRNAs controls when and how much RNA is created. Due to technical limitations, the protein level expressions of TFs are usually unknown, making computational reconstruction of transcriptional network a difficult task. We proposed here a novel Bayesian non-negative hybrid factor model for(More)
Alveolar rhabdomyosarcoma (aRMS) is a myogenic childhood sarcoma frequently associated with a translocation-mediated fusion gene, Pax3:Foxo1a. We investigated the complementary role of Rb1 loss in aRMS tumor initiation and progression using conditional mouse models. Rb1 loss was not a necessary and sufficient mutational event for rhabdomyosarcomagenesis,(More)