Sentence examples for develop gene expression from inspiring English sources

Gene expression analysis has been used to develop gene expression signatures that predict clinical outcome in breast cancer patients [ 5- 9].

It is essential to develop gene expression system that allows high level expression of quality proteins both in research and therapeutic purposes.

A number of studies have been conducted in CRC, often in a supervised fashion, to develop gene expression signatures capable of identifying patient populations at high risk of recurrence [ 18- 26].

The statistical methods used here to develop gene expression signatures of pathway activity have been previously described [ 4] and are described in detail in the Additional file 2 Methods.

To develop gene expression profiles that characterise KRAS-, BRAF- or PIK3CA-activated- tumours, and to explore whether these profiles might be helpful in predicting the response to the epidermal growth factor receptor (EGFR) pathway inhibitors better than mutation status alone.

Methods have also been proposed to develop gene expression networks using dynamical systems defined by ordinary differential equations (Chen et al. 1999), modified linear regression methods (Gardner et al. 2003), Boolean networks (Akutsu et al. 2000) where gene expression data are converted to two states (ON and OFF), discrete networks (Hartemink et al. 2002), and many others.

Little is known of the regulatory architecture that is responsible for Dlx gene expression in developing arches.

Some approaches have nonetheless been developed to exploit information from gene expression data using models.

Our goal is to identify small, clinically-relevant gene subsets to develop gene expression-based tests and gain insight into the interrelationships between these genes and clinical outcome.

Owing to the substantial molecular differences that exist between poor prognosis and good prognosis ER-positive cancers that are driven by the large number of genes involved in regulating and executing cell proliferation, it is relatively easy to develop gene expression-based prognostic predictors for ER-positive cancers.

METHODS: Using in vitro drug sensitivity data, coupled with microarray data, we developed gene expression signatures predicting sensitivity to cisplatin and pemetrexed.