A data analysis framework for biomedical big data: Application on mesoderm differentiation of human pluripotent stem cells.

ABSTRACT: The development of high-throughput biomolecular technologies has resulted in generation of vast omics data at an unprecedented rate. This is transforming biomedical research into a big data discipline, where the main challenges relate to the analysis and interpretation of data into new biological knowledge. The aim of this study was to develop a framework for biomedical big data analytics, and apply it for analyzing transcriptomics time series data from early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. To this end, transcriptome profiling by microarray was performed on differentiating human pluripotent stem cells sampled at eleven consecutive days. The gene expression data was analyzed using the five-stage analysis framework proposed in this s

SUBMITTER: Ulfenborg B 

PROVIDER: S-EPMC5487013 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature