Sentence examples for multiple tumor samples from inspiring English sources

Microarray analysis of multiple tumor samples suggested a link between RNF13 expression and various human tumors including melanoma (Jin et al., 2011).

Analyses of common integration sites across multiple tumor samples have identified putative cancer genes associated with the various types of neoplasms in the mouse T2/Onc-induced cancers.

Lu et al. [ 39] analyzed the miRNA expression profile from multiple tumor samples.

Second, by analyzing multiple tumor samples from each patient, we have addressed the fact that metastatic prostate cancer shows significant heterogeneity, even within the same patient [ 21].

Assays of multiple tumor samples frequently reveal recurrent genomic aberrations, including point mutations and copy-number alterations, that affect individual genes.

This was particularly important in these studies that used a relatively complex design with on-chip and inter-chip probe replication, multiple tumor samples and tumor types, dye-swap and a common reference RNA sample for all hybridizations.

Finally, the method by Tolliver et al. requires multiple tumor-samples (distinct patients) as an input, whereas EXPANDS predicts SPs independently, from sequencing data obtained from individual patients.

By measuring gene expression levels related to multiple individuals and multiple tissue or tumor samples, investigators can discover molecular markers to be used for cancer diagnosis, prognosis, and prediction.

These results confirmed that the multiple isoforms observed in tumor samples exhibited a prevalence associated with differential N-linked glycosylation (Fig. 6A and B).

One possibility could be using circulating tumor cells, known as liquid biopsies, to reduce the confounding effect of sampling multiple tumor nodules in a prostate gland and improve the current biopsy strategy [ 54, 55].

Recently, Oesper et al. investigated tumor heterogeneity using DNA sequencing data and showed that multiple tumor subclones may often exist in tumor samples (Oesper et al., 2013), suggesting that tumor heterogeneity is another key factor in interpreting tumor sequencing data.