title: Visualizing quantitative microscopy data: History and challenges.
abstract: Data visualization is a fundamental aspect of science. In the context of microscopy-based studies, visualization typically involves presentation of the images themselves. However, data visualization is challenging when microscopy experiments entail imaging of millions of cells, and complex cellular phenotypes are quantified in a high-content manner. Most well-established visualization tools are inappropriate for displaying high-content data, which has driven the development of new visualization methodology. In this review, we discuss how data has been visualized in both classical and high-content microscopy studies; as well as the advantages, and disadvantages, of different visualization methods.
authors.affiliation: a Department of Engineering Science , University of Oxford , Oxford , UK .
authors.forename: Heba Z
authors.initials: HZ
authors.lastname: Sailem
authors.affiliation: b Department of Computational Systems Medicine , Imperial College, South Kensington Campus , London , UK , and.|c Division of Cancer Biology , Chester Beatty Laboratories, Institute of Cancer Research , London , UK.
authors.forename: Sam
authors.initials: S
authors.lastname: Cooper
authors.affiliation: c Division of Cancer Biology , Chester Beatty Laboratories, Institute of Cancer Research , London , UK.
authors.forename: Chris
authors.initials: C
authors.lastname: Bakal
mesh_terms: D045744:Cell Line, Tumor; D006801:Humans; D008853:Microscopy
keywords: Cell phenotypes; data visualization; high-content analysis; microscopy