Learn More
Osteoarthritis (OA) is characterized by remodeling and degradation of joint tissues. Microarray studies have led to a better understanding of the molecular changes that occur in tissues affected by conditions such as OA; however, such analyses are limited to the identification of a list of genes with altered transcript expression, usually at a single time(More)
OBJECTIVE To better understand the contribution of age to the development of osteoarthritis (OA). METHODS Surgical destabilization of the medial meniscus (DMM) was used to model OA in 12-week-old and 12-month-old male C57BL/6 mice. OA severity was evaluated histologically. RNA used for microarray and real-time polymerase chain reaction analysis was(More)
To identify gene products that participate in auxin-dependent lateral root formation, a high temporal resolution, genome-wide transcript abundance analysis was performed with auxin-treated Arabidopsis thaliana roots. Data analysis identified 1246 transcripts that were consistently regulated by indole-3-acetic acid (IAA), partitioning into 60 clusters with(More)
Osteoarthritis (OA) is the most common form of arthritis and has multiple risk factors including joint injury. The purpose of this study was to characterize the histologic development of OA in a mouse model where OA is induced by destabilization of the medial meniscus (DMM model) and to identify genes regulated during different stages of the disease, using(More)
Angiogenesis is one of the hallmarks of cancer and is essential for cancer progression and metastasis. However, clinical trials with vascular endothelial growth factor (VEGF) pathway inhibitors have failed to show overall survival benefit in breast cancer. Targeted therapy against the angiopoietin pathway, a downstream angiogenesis cascade, could be(More)
Clustering analysis is an important exploratory tool that aids in the analysis and organization of genomic data. Each biological data set has different characteris, and the decision of which clustering method is appropriate and how many clusters are optimal on a dataset-by-dataset basis can be problematic. The Figure of Merit (FOM) is a quantitative(More)
Dendritic cells (DC) play a central role in primary immune responses and become potent stimulators of the adaptive immune response after undergoing the critical process of maturation. Understanding the dynamics of DC maturation would provide key insights into this important process. Time course microarray experiments can provide unique insights into DC(More)
Human papillomavirus (HPV) DNA is detected in up to 80% of oropharyngeal carcinomas (OPC) and this HPV positive disease has reached epidemic proportions. To increase our understanding of the disease, we investigated the status of the HPV16 genome in HPV-positive head and neck cancers (HNC). Raw RNA-Seq and Whole Genome Sequence data from The Cancer Genome(More)
UNLABELLED Standard and Consensus Clustering Analysis Tool for Microarray Data (SC²ATmd) is a MATLAB-implemented application specifically designed for the exploration of microarray gene expression data via clustering. Implementation of two versions of the clustering validation method figure of merit allows for performance comparisons between different(More)
AIMS The central issue of resistance to radiation remains a significant challenge in the treatment of cancer despite improvements in treatment modality and emergence of new therapies. To facilitate the identification of molecular factors that elicit protection against ionizing radiation, we developed a matched model of radiation resistance for head and neck(More)