These data might anticipate in elucidating cell signaling and pathophysiological pathways.
The acquirement of accurate epidemiological data is crucial in elucidating the natural course and prognosis of IPF in different populations, and can lead to a better understanding of the disease etiology.
Indeed, other authors have reported a similar approach in particular with Carcinomas of Unknown Primary (CUP) [ 21], suggesting that expression data may help in elucidating the histogenetic origin of metastatic tissue.
The greater risk of death linked to dermatomyositis accompanied by neoplasm was consistent with the results of an earlier study [ 58], in which the mortality data were decisive in elucidating the risk of neoplasm in patients with dermatomyositis [ 34, 58, 59].
These data will be useful in elucidating the environmental, metabolic and genetic conditions, and to investigate the complex interactions that underlie RAP and CP.
Fortunately, recent advances in RNA-seq technology have increased its potential in generating functional "omics data" and thus help in elucidating the molecular basis for key developmental processes.
Whereas BBDR models based on in vivo data have proved useful in elucidating mechanisms of action of toxic chemicals and identifying knowledge gaps, they have not proved to be useful in estimating low-dose risks in the range of risks required for setting exposure standards (e.g., 10−3 and lower).
We believe that these novel data will prove highly valuable in elucidating the genetic alterations in various cancers, as well as offering potential directions for new approaches in diagnostics and therapeutics.
Given the importance of such pathway in a wide variety of cellular processes, our data is a key step in elucidating the biological networks that, in part, direct the pathogenicity of these parasites resulting in a massive impact on global health.
Microarray data has been widely used in elucidating biological mechanisms, specifically in discovering functional modules, pathways (Bar-Joseph et al., 2003; Segal et al., 2003a) and reverse engineering regulatory networks (Hartemink, 2005; Margolin et al., 2006; Segal et al., 2003c).
