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Data generation is no longer the limiting factor in advancing biological research. In addition, data integration, analysis, and interpretation have become key bottlenecks and challenges that biologists conducting genomic research face daily. To enable biologists to derive testable hypotheses from the increasing amount of genomic data, we have developed the(More)
Understanding how nutrients affect gene expression will help us to understand the mechanisms controlling plant growth and development as a function of nutrient availability. Nitrate has been shown to serve as a signal for the control of gene expression in Arabidopsis. There is also evidence, on a gene-by-gene basis, that downstream products of nitrogen (N)(More)
Light and carbon are two important interacting signals affecting plant growth and development. The mechanism(s) and/or genes involved in sensing and/or mediating the signaling pathways involving these interactions are unknown. This study integrates genetic, genomic and systems approaches to identify a genetically perturbed gene network that is regulated by(More)
Nitrate-induced reprogramming of the transcriptome has recently been shown to be highly context dependent. Herein, a systems biology approach was developed to identify the components and role of cross-talk between nitrate and hormone signals, likely to be involved in the conditional response of NO3- signaling. Biclustering was used to identify a set of(More)
BACKGROUND AND AIM To investigate the impact of hospital-acquired Clostridium difficile infection (CDI) on hospital costs and patient length of stay. METHODS Data from the 2007-2008 New York State Department of Health's Statewide Planning and Research Cooperative System (SPARCS) database was analyzed using regression analysis and descriptive statistics.(More)
CONTEXT This article investigates the financial impact of the Centers for Medicare & Medicaid Services' hospital-acquired conditions (HACs). METHODS Data from 2007-2008 was analyzed using New York State Department of Health's Statewide Planning and Research Cooperative System (SPARCS), using regression analysis and descriptive statistics for each(More)
Prediction of transcriptional regulatory mechanisms in Arabidopsis has become increasingly critical with the explosion of genomic data now available for both gene expression and gene sequence composition. We have shown in previous work [1], that a combination of correlation measurements and cis-regulatory element (CRE) detection methods are effective in(More)
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