Background: Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer related death in the world with a five-year survival rate of less than 5%. Not all PDAC are the same, because there exist intra-tumoral heterogeneity between PDAC, which poses a great challenge to personalized treatments for PDAC.
Methods: To dissect the molecular heterogeneity of PDAC, we performed a retrospective meta-analysis on whole transcriptome data from more than 1200 PDAC patients.
Co-clustering, often called biclustering for two-dimensional data, has found many applications, such as gene expression data analysis and text mining. Nowadays, a variety of multi-dimensional arrays (tensors) frequently occur in data analysis tasks, and co-clustering techniques play a key role in dealing with such datasets. Co-clusters represent coherent patterns and exhibit important properties along all the modes.
View Article and Find Full Text PDFTachyplesin I is a 17 amino acid, cationic, antimicrobial peptide with a typical cyclic antiparallel β-sheet structure. Interactions of tachyplesin I with living bacteria are not well understood, although models have been used to elucidate how tachyplesin I permeabilizes membranes. There are several questions to be answered, such as (i) how does tachyplesin I kill bacteria after it penetrates the membrane and (ii) does bacterial death result from the inactivation of intracellular esterases as well as cell injury? In this study, the dynamic antibacterial processes of tachyplesin I and its interactions with Escherichia coli and Staphylococcus aureus were investigated using laser confocal scanning microscopy in combination with electron microscopy.
View Article and Find Full Text PDFComput Math Methods Med
December 2014
Tachyplesin I (TP I) is an antimicrobial peptide isolated from the hemocytes of the horseshoe crab. With the developments of DNA microarray technology, the genetic analysis of the toxic effect of TP I on embryo was originally considered in our recent study. Based on our microarray data of the embryonic samples of zebrafish treated with the different doses of TP I, we performed a series of statistical data analyses to explore the toxic effect of TP I at the genomic level.
View Article and Find Full Text PDFPredicting disease progression is one of the most challenging problems in prostate cancer research. Adding gene expression data to prediction models that are based on clinical features has been proposed to improve accuracy. In the current study, we applied a logistic regression (LR) model combining clinical features and gene co-expression data to improve the accuracy of the prediction of prostate cancer progression.
View Article and Find Full Text PDFIdentifying genes associated with cancer development is typically accomplished by comparing mean expression values in normal and tumor tissues, which identifies differentially expressed (DE) genes. Interindividual variation (IV) in gene expression is indirectly included in DE gene identification because given the same absolute differences in means, genes with lower variance tend to have lower p-values. We explored the direct use of IV in gene expression to identify candidate genes associated with cancer development.
View Article and Find Full Text PDFIEEE/ACM Trans Comput Biol Bioinform
September 2011
The effects of a drug on the genomic scale can be assessed in a three-color cDNA microarray with the three color intensities represented through the so-called hexaMplot. In our recent study, we have shown that the Hough Transform (HT) applied to the hexaMplot can be used to detect groups of coexpressed genes in the normal-disease-drug samples. However, the standard HT is not well suited for the purpose because 1) the assayed genes need first to be hard-partitioned into equally and differentially expressed genes, with HT ignoring possible information in the former group; 2) the hexaMplot coordinates are negatively correlated and there is no direct way of expressing this in the standard HT and 3) it is not clear how to quantify the association of coexpressed genes with the line along which they cluster.
View Article and Find Full Text PDFBackground: The genetic control of prostate cancer development is poorly understood. Large numbers of gene-expression datasets on different aspects of prostate tumorigenesis are available. We used these data to identify and prioritize candidate genes associated with the development of prostate cancer and bone metastases.
View Article and Find Full Text PDFPhys Rev E Stat Nonlin Soft Matter Phys
October 2009
DNA rigidity is an important physical property originating from the DNA three-dimensional structure. Although the general DNA rigidity patterns in human promoters have been investigated, their distinct roles in transcription are largely unknown. In this paper, we discover four highly distinct human promoter groups based on similarity of their rigidity profiles.
View Article and Find Full Text PDFBackground: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increasingly popular to solve this type of problems. These models show good performance in accommodating noise, variability and low replication of microarray data.
View Article and Find Full Text PDFBiclustering is an important tool in microarray analysis when only a subset of genes co-regulates in a subset of conditions. Different from standard clustering analyses, biclustering performs simultaneous classification in both gene and condition directions in a microarray data matrix. However, the biclustering problem is inherently intractable and computationally complex.
View Article and Find Full Text PDFBMC Bioinformatics
July 2007
Background: Three-color microarray experiments can be performed to assess drug effects on the genomic scale. The methodology may be useful in shortening the cycle, reducing the cost, and improving the efficiency in drug discovery and development compared with the commonly used dual-color technology. A visualization tool, the hexaMplot, is able to show the interrelations of gene expressions in normal-disease-drug samples in three-color microarray data.
View Article and Find Full Text PDFYing Yong Sheng Tai Xue Bao
February 2006
Based on the study of pollen, stratum and 14C dating of Daqiao fen in Dunhua of Jilin Province, four pollen zones were distinguished, i.e., Pinus-Picea-Abies assemblage (2195 +/- 70 to appromimately 2045 +/- 70 B.
View Article and Find Full Text PDFDNA microarray offers a powerful and effective technology to monitor the changes in the gene expression levels for thousands of genes simultaneously. It is being widely applied to explore the quantitative alternation in gene regulation in response to a variety of aspects including diseases and exposure of toxicant. A common task in analyzing microarray data is to identify the differentially expressed genes under two different experimental conditions.
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