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As context is important to gene expression, so is the preprocessing of microarray to transcriptomics. Microarray data suffers from several normalization and significance problems. Arbitrary fold change (FC) cut-offs of >2 and significance p-values of <0.02 lead data collection to look only at genes which vary wildly amongst other genes. Therefore, questions(More)
A treecode algorithm is presented for rapid computation of the nonbonded potential energy in classical molecular systems. The algorithm treats a general form of pairwise particle interaction with the Coulomb and London dispersion potentials as special cases. The energy is computed as a sum of group–group interactions using a variant of Appel's recursive(More)
BACKGROUND Hedgehog (HH) signaling plays a critical role in normal cellular processes, in normal mammalian gastrointestinal development and differentiation, and in oncogenesis and maintenance of the malignant phenotype in a variety of human cancers. Increasing evidence further implicates the involvement of HH signaling in oncogenesis and metastatic behavior(More)
BACKGROUND Renal cell carcinoma (RCC) is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of(More)
Analysis of gene expression data provides an objective and efficient technique for sub-classification of leukemia. The purpose of the present study was to design a committee neural networks based classification systems to subcategorize leukemia gene expression data. In the study, a binary classification system was considered to differentiate acute(More)
Lung cancer is the second most commonly occurring non-cutaneous cancer in the United States with the highest mortality rate among both men and women. In this study, we utilized three lung cancer microarray datasets generated by previous researchers to identify differentially expressed genes, altered signaling pathways, and assess the involvement of Hedgehog(More)
BACKGROUND One main research challenge in the post-genomic era is to understand the relationship between protein sequences and their biological functions. In recent years, several automated annotation systems have been developed for the functional assignment of uncharacterized proteins. The underlying assumption of these systems is that similar sequences(More)
In this paper, we discuss an efficient parallel implementation of the treecode Ewald method for fast evaluation of long-range Coulomb interactions in a periodic system for molecular dynamics simulations. The parallelization is based on an adaptive decomposition scheme using the Morton order of the particles. This decomposition scheme takes advantage of the(More)
Numerous genome projects have produced a large and ever increasing amount of genomic sequence data. However, the biological functions of many proteins encoded by the sequences remain unknown. Protein function annotation and prediction become an essential and challenging task of post-genomic research. In this paper, we present an automated protein function(More)
Microarray gene expression profiles of both renal cell carcinoma (RCC) tissues and a RCC cell line were analyzed using singular value decomposition (SVD) and functional clustering. The SVD projections of the expression profiles revealed significant differences between the profiles of RCC tissues and a RCC cell line. Based on the biological processes ,(More)