Sentence examples for sample for identifying from inspiring English sources
Bipolar disorder in children and adolescents is characterized by increased stress reactivity and frequent episodes of shorter duration; thus our cohort provides a potentially enriched sample for identifying genes involved in cycling and switching.
The literature also strongly recommends stratified random sampling for identifying the test samples.
Diagnostic accuracy can possibly be improved by using duplicate or triplicate samples for identifying quarters at risk and, subsequently, incident IMI.
These results demonstrate that macrodissection-based gene expression analyses outperformed gene expression analyses from LCM samples for identifying genes overexpressed in gastric cancer.
We adopted the normalized RNA Seq V2 RSEM data of the 3299 TCGA samples for identifying genes with significant subgroup-specific expression changes.
Using prostate cancer as an example, we have assessed the use of different kinds and amounts of tissue samples for identifying genetic variations.
Using the same samples for identifying both ASE and cis-eQTL was thus essential for avoiding inter-sample biases and additional effects induced by the exceptionally high heterozygosity of F1 s.
Only the recent hierarchical hidden Markov model (H-HMM) (Shah et al., 2007) and fused SVM (Rapaport et al., 2008) models demonstrate the benefits of supervised sequential array-CGH analysis over many tumor samples for identifying clinically important regions of aneuploidy, but identifying the causal genes within these amplicons remains an open challenge.
We believe that it may be rather optimistic to set a minimum number of samples for identifying significant aberrations at, for instance, 33% because this would easily ignore (not detect) rare breast cancer subtypes that tend to be under-represented in any particular study.
Adequacy of sample size for identifying the risk factors for IRE was based on a preliminary examination of a subset of the children.
Investigators have reported difficulties caused by sample heterogeneity for identifying biologically relevant differentially expressed genes and for developing and validating predictive models [ 1- 3].
