Communicating genome architecture: biovisualization of the genome, from data analysis and hypothesis generation to communication and learning

Goodstadt, Mike N.; Marti-Renom, Marc A.

doi:http://dx.doi.org/10.1016/j.jmb.2018.11.008

Communicating genome architecture: biovisualization of the genome, from data analysis and hypothesis generation to communication and learning

Citation

Goodstadt MN, Marti-Renom MA. Communicating genome architecture: biovisualization of the genome, from data analysis and hypothesis generation to communication and learning. J Mol Biol. 2019;431(6):1071-87. DOI: 10.1016/j.jmb.2018.11.008

Abstract

Genome discoveries at the core of biology are made by visual description and exploration of the cell, from microscopic sketches and biochemical mapping to computational analysis and spatial modeling. We outline the experimental and visualization techniques that have been developed recently which capture the three-dimensional interactions regulating how genes are expressed. We detail the challenges faced in integration of the data to portray the components and organization and their dynamic landscape. The goal is more than a single data-driven representation as interactive visualization for de novo research is paramount to decipher insights on genome organization in space.