GEMS: a web server for biclustering analysis of expression data

The advent of microarray technology has revolutionized the search for genes that are differentially expressed across a range of cell types or experimental conditions. Traditional clustering methods, such as hierarchical clustering, are often difficult to deploy effectively since genes rarely exhibit similar expression pattern across a wide range of conditions. Biclustering of gene expression data (also called co-clustering or two-way clustering) is a non-trivial but promising methodology for the identification of gene groups that show a coherent expression profile across a subset of conditions. Thus, biclustering is a natural methodology as a screen for genes that are functionally related, participate in the same pathways, affected by the same drug or pathological condition, or genes that form modules that are potentially co-regulated by a small group of transcription factors. We have developed a web-enabled service called GEMS (Gene Expression Mining Server) for biclustering microarray data. Users may upload expression data and specify a set of criteria. GEMS then performs bicluster mining based on a Gibbs sampling paradigm. The web server provides a flexible and an useful platform for the discovery of co-expressed and potentially co-regulated gene modules. GEMS is an open source software and is available at

GEMS: a web server for biclustering analysis of expression data

The advent of microarray technology has revolutionized the search for genes that are differentially expressed across a range of cell types or experimental conditions. Traditional clustering methods, such as hierarchical clustering, are often difficult to deploy effectively since genes rarely exhibit similar expression pattern across a wide range of conditions. Biclustering of gene expression data (also called co-clustering or two-way clustering) is a non-trivial but promising methodology for the identification of gene groups that show a coherent expression profile across a subset of conditions. Thus, biclustering is a natural methodology as a screen for genes that are functionally related, participate in the same pathways, affected by the same drug or pathological condition, or genes that form modules that are potentially co-regulated by a small group of transcription factors. We have developed a web-enabled service called GEMS (Gene Expression Mining Server) for biclustering microarray data. Users may upload expression data and specify a set of criteria. GEMS then performs bicluster mining based on a Gibbs sampling paradigm. The web server provides a flexible and an useful platform for the discovery of co-expressed and potentially co-regulated gene modules. GEMS is an open source software and is available at

A Sliding-Window Approach to Mining Maximal Large Itemsets for Large Databases

In this paper, we propose a Sliding-Window approach, the SWMax algorithm, which could provide good performance for both mining maximal itemsets and incremental mining. Our SWMax algorithm is a two-passes partition-based approach. For incremental mining, if an itemset with size equal to 1 is not large in the original database, it could not be found in the updated database based on the SWF algorithm. Our SWMax algorithm will support incremental mining correctly. From our simulation, the results show that our SWMax algorithm could generate fewer number of candidates and needs less time than the SWF algorithm

A Predictive Phosphorylation Signature of Lung Cancer

Background: Aberrant activation of signaling pathways drives many of the fundamental biological processes that accompany tumor initiation and progression. Inappropriate phosphorylation of intermediates in these signaling pathways are a frequently observed molecular lesion that accompanies the undesirable activation or repression of pro- and anti-oncogenic pathways. Therefore, methods which directly query signaling pathway activation via phosphorylation assays in individual cancer biopsies are expected to provide important insights into the molecular “logic” that distinguishes cancer and normal tissue on one hand, and enables personalized intervention strategies on the other. Results: We first document the largest available set of tyrosine phosphorylation sites that are, individually, differentially phosphorylated in lung cancer, thus providing an immediate set of drug targets. Next, we develop a novel computational methodology to identify pathways whose phosphorylation activity is strongly correlated with the lung cancer phenotype. Finally, we demonstrate the feasibility of classifying lung cancers based on multi-variate phosphorylation signatures. Conclusions: Highly predictive and biologically transparent phosphorylation signatures of lung cancer provide evidence for the existence of a robust set of phosphorylation mechanisms (captured by the signatures) present in the majority of lung cancers, and that reliably distinguish each lung cancer from normal. This approach should improve our understanding of cancer and help guide its treatment, since the phosphorylation signatures highlight proteins and pathways whose phosphorylation should be inhibited in order to prevent unregulated proliferation

An In Vivo Screen Identifies PYGO2 as a Driver for Metastatic Prostate Cancer

Advanced prostate cancer displays conspicuous chromosomal instability and rampant copy number aberrations, yet the identity of functional drivers resident in many amplicons remain elusive. Here, we implemented a functional genomics approach to identify new oncogenes involved in prostate cancer progression. Through integrated analyses of focal amplicons in large prostate cancer genomic and transcriptomic datasets as well as genes upregulated in metastasis, 276 putative oncogenes were enlisted into an in vivo gain-of-function tumorigenesis screen. Among the top positive hits, we conducted an in-depth functional analysis on Pygopus family PHD finger 2 (PYGO2), located in the amplicon at 1q21.3. PYGO2 overexpression enhances primary tumor growth and local invasion to draining lymph nodes. Conversely, PYGO2 depletion inhibits prostate cancer cell invasion in vitro and progression of primary tumor and metastasis in vivo In clinical samples, PYGO2 upregulation associated with higher Gleason score and metastasis to lymph nodes and bone. Silencing PYGO2 expression in patient-derived xenograft models impairs tumor progression. Finally, PYGO2 is necessary to enhance the transcriptional activation in response to ligand-induced Wnt/β-catenin signaling. Together, our results indicate that PYGO2 functions as a driver oncogene in the 1q21.3 amplicon and may serve as a potential prognostic biomarker and therapeutic target for metastatic prostate cancer.Significance: Amplification/overexpression of PYGO2 may serve as a biomarker for prostate cancer progression and metastasis. Cancer Res; 78(14); 3823-33. ©2018 AACR

Examining the Relationship between Cardiorespiratory Fitness and Body Weight Status: Empirical Evidence from a Population-Based Survey of Adults in Taiwan

Background. Cardiovascular disease is the number one cause of death worldwide. Meanwhile, obesity has been recognized as a global epidemic. This study aims to examine the extent to which cardiorespiratory fitness is associated with body mass among adult males and females in Taiwan. Materials and Methods. A nationally representative dataset consisting of 68,175 adults aged 18–60, including 31,743 males and 36,432 females, was used. Several multivariate regression models were used to investigate the relationship between cardiorespiratory fitness and body weight status, after controlling for adults’ sociodemographic status. Results. A one-unit increase in the BMI lowered the cardiorespiratory fitness score by 0.316 and 0.368 points for adult males and females, respectively. Among adult males, compared to those of normal weight, adult males who were underweight, overweight, or obese had a lower cardiorespiratory fitness score by 1.287, 0.845, and 3.353 points, respectively. Similar results could be found in female samples. Conclusion. The overweight and obese adults had much lower levels of cardiorespiratory fitness as compared to their normal weight counterparts. Given the upward trend in the prevalence of overweight and obesity, it is important to help overweight and obese people to become more fit and reach their healthy weight

AMiBA: scaling relations between the integrated Compton-y and X-ray derived temperature, mass, and luminosity

We investigate the scaling relations between the X-ray and the thermal Sunyaev-Zel'dovich Effect (SZE) properties of clusters of galaxies, using data taken during 2007 by the Y.T. Lee Array for Microwave Background Anisotropy (AMiBA) at 94 GHz for the six clusters A1689, A1995, A2142, A2163, A2261, and A2390. The scaling relations relate the integrated Compton-y parameter Y_{2500} to the X-ray derived gas temperature T_{e}, total mass M_{2500}, and bolometric luminosity L_X within r_{2500}. Our results for the power-law index and normalization are both consistent with the self-similar model and other studies in the literature except for the Y_{2500}-L_X relation, for which a physical explanation is given though further investigation may be still needed. Our results not only provide confidence for the AMiBA project but also support our understanding of galaxy clusters.Comment: Accepted by ApJ; 8 pages, 3 figures, 5 table

AMiBA Wideband Analog Correlator

A wideband analog correlator has been constructed for the Yuan-Tseh Lee Array for Microwave Background Anisotropy. Lag correlators using analog multipliers provide large bandwidth and moderate frequency resolution. Broadband IF distribution, backend signal processing and control are described. Operating conditions for optimum sensitivity and linearity are discussed. From observations, a large effective bandwidth of around 10 GHz has been shown to provide sufficient sensitivity for detecting cosmic microwave background variations.Comment: 28 pages, 23 figures, ApJ in press

AMiBA: Broadband Heterodyne CMB Interferometry

The Y. T. Lee Array for Microwave Background (AMiBA) has reported the first science results on the detection of galaxy clusters via the Sunyaev Zel'dovich effect. The science objectives required small reflectors in order to sample large scale structures (20') while interferometry provided modest resolutions (2'). With these constraints, we designed for the best sensitivity by utilizing the maximum possible continuum bandwidth matched to the atmospheric window at 86-102GHz, with dual polarizations. A novel wide-band analog correlator was designed that is easily expandable for more interferometer elements. MMIC technology was used throughout as much as possible in order to miniaturize the components and to enhance mass production. These designs will find application in other upcoming astronomy projects. AMiBA is now in operations since 2006, and we are in the process to expand the array from 7 to 13 elements.Comment: 10 pages, 6 figures, ApJ in press; a version with high resolution figures available at http://www.asiaa.sinica.edu.tw/~keiichi/upfiles/AMiBA7/mtc_highreso.pd