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BackgroundNumerous studies have examined gene × environment interactions (G × E) in cognitive and behavioral domains. However, these studies have been limited in that they have not been able to directly assess differential patterns of gene expression in the human brain. Here, we assessed G × E interactions using two publically available datasets to assess if DNA variation is associated with post‐mortem...
We propose a signal processing approach for detecting enrichment regions from ChIP-seq datasets. A wavelet transform of the ChIP-seq data offers a direct visualization for both short- and long-range patterns of the genome-wide mapping profile for protein binding site on DNA. To investigate the location of transcription factor binding site (TFBS) from ChIP-seq data, a wavelet-based peak detection algorithm...
Enabling data analysis in large data depositories for high throughput experimental data such as gene microarrays and ChIP-seq is challenging. In this paper, we discuss three methods for integrating QUEST, a data depository for epigenetic experiments, with a web-based data analysis platform GenePattern. These methods are universal and can serve as an exemplary implementation resolving the dilemma facing...
In this paper, we investigated the use of gene coexpression network analyses to identify potential biomarkers for breast carcinoma prognosis. The network mining algorithm CODENSE is used to identify highly connected genome-wide gene co-expression networks among a variety of cancer types, and the resulted gene clusters are applied to a series of breast cancer microarray sets to categorize the patients...
We are developing a new framework for discovery of genes involved in the breast carcinogenesis process. Among families that have a predisposition to breast cancer, approximately 25% have inherited mutations in either breast cancer associated (ldquoBRCArdquo) genes BRCA1 or BRCA2, but the predisposing mutated genes in the majority of the families are unknown. BRCA1 and BRCA2 gene products both regulate...
New high-throughput sequencing technologies can generate millions of short DNA sequences that need to be mapped to the reference genome accurately. Majority of the mapping algorithms handle variations in the quality of these short sequences by allowing more mismatches and/or gaps in the alignment and focus to improve runtime. In this paper, we investigate ways to classify quality scores of short DNA...
In this paper we report an ongoing project for identifying human cytomegalovirus (HCMV) micro RNAs (miRNA) expressed in infected human cells using the new massive parallel sequencing technology with the Solexa Sequencer. We developed a data processing pipeline for analyzing such data including mapping segments to genomes, detecting highly expressed sequences and their loci, comparing sequences to...
The computational power and memory bandwidth of graphics processing units (GPUs) have turned them into attractive platforms for general-purpose applications. In this paper, we exploit this power in the context of biomedical image processing by establishing a cooperative environment between the CPU and the GPU. We deal with phenotype and color analysis on a wide variety of microscopic images from studies...
We present an application problem of examining phenotype differences in wildtype and retinoblastoma (Rb) knockout specimens of mouse placenta. The lack of the Rb gene causes uncontrolled tissue growth which forces infiltrations into critical sections of mouse placenta that lead to fetal death. We briefly describe our method for volume visualization of mouse placenta tissue level intermixing at a microscopic...
Microscopic imaging is an important phenotyping tool to characterize the phenotype (e.g., morphology and behavior) change caused by genotype manipulation such as mutation and gene knockout. Recently we use high resolution microscopic imaging to study the morphological change on mouse placenta induced by retinoblast (Rb) gene knockout. In order to assess the morphological change we first segment each...
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