0000000000143263
AUTHOR
Charles Wang
Comparison of RNA-seq and microarray-based models for clinical endpoint prediction
Background Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. Results We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being …
Study of the Ti44(α,p)V47 reaction and implications for core collapse supernovae
The underlying physics triggering core collapse supernovae is not fully understood but observations of material ejected during such events helps to solve this puzzle. In particular, several satellite based γ-ray observations of the isotope 44Ti have been reported recently. Conveniently, the amount of this isotope in stellar ejecta is thought to depend critically on the explosion mechanism. The most influential reaction to the amount of 44Ti in supernovae is Ti44(α,p)V47. Here we report on a direct study of this reaction conducted at the REX-ISOLDE facility, CERN. The experiment was performed with a 44Ti beam at Elab = 2.16MeV/u, corresponding to an energy distribution, for reacting α-partic…