Uncovering extensive post-translation regulation during human cell cycle progression by integrative multi-'omics analysis.

ABSTRACT:

Background

Analysis of high-throughput multi-'omics interactions across the hierarchy of expression has wide interest in making inferences with regard to biological function and biomarker discovery. Expression levels across different scales are determined by robust synthesis, regulation and degradation processes, and hence transcript (mRNA) measurements made by microarray/RNA-Seq only show modest correlation with corresponding protein levels.

Results

In this work we are interested in quantitative modelling of correlation across such gene products. Building on recent work, we develop computational models spanning transcript, translation and protein levels at different stages of the H. sapiens cell cycle. We enhance this analysis by incorporating 25+ sequence-derived features

SUBMITTER: Parkes GM 

PROVIDER: S-EPMC6820968 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature