Stems Cells, Big Data and Compendium-based Analyses for Identifying Cell Types, Signalling Pathways and Gene Regulatory Networks

Overview

Journal Biophys Rev

Publisher Springer

Specialty Biophysics

Date 2019 Jan 27

PMID 30684132

Citations 3

Authors

Md Humayun Kabir

Michael D OConnor

Affiliations

Soon will be listed here.

Abstract

Identification of new drug and cell therapy targets for disease treatment will be facilitated by a detailed molecular understanding of normal and disease development. Human pluripotent stem cells can provide a large in vitro source of human cell types and, in a growing number of instances, also three-dimensional multicellular tissues called organoids. The application of stem cell technology to discovery and development of new therapies will be aided by detailed molecular characterisation of cell identity, cell signalling pathways and target gene networks. Big data or 'omics' techniques-particularly transcriptomics and proteomics-facilitate cell and tissue characterisation using thousands to tens-of-thousands of genes or proteins. These gene and protein profiles are analysed using existing and/or emergent bioinformatics methods, including a growing number of methods that compare sample profiles against compendia of reference samples. This review assesses how compendium-based analyses can aid the application of stem cell technology for new therapy development. This includes via robust definition of differentiated stem cell identity, as well as elucidation of complex signalling pathways and target gene networks involved in normal and diseased states.

Citing Articles

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