System-level measurement, modeling, and manipulation of RNA
- Mihaela Zavolan1,2 and
- Gene W. Yeo3,4
- 1Biozentrum, University of Basel, CH-4056 Basel, Switzerland
- 2Swiss Institute of Bioinformatics, Biozentrum, University of Basel, CH-4056 Basel, Switzerland
- 3University of California San Diego, La Jolla, California 92093, USA
- 4Sanford Consortium for Regenerative Medicine, La Jolla, California 92037, USA
- Corresponding authors: mihaela.zavolan{at}unibas.ch; geneyeo{at}ucsd.edu
This extract was created in the absence of an abstract.
In the two and a half decades since the sequencing of the human genome, we have witnessed an explosion in technologies designed to interrogate how genetic information unfolds within a human body in space and time, during development and aging, across healthy and diseased tissues. We can now simultaneously measure the abundance, localization, modification status, and protein output of all RNAs expressed in a single cell for millions of cells, as well as carry out functional screens of hundreds of thousands of sequence variants. These measurements almost always rely on identifying nucleic acid sequences and their variants, usually by sequencing. Naturally, the large volumes of data that are generated within individual experiments can only be interpreted with appropriate computational analysis methods. In this area too, there has been tremendous development, especially since the broad adoption of machine learning and AI approaches specifically designed to take advantage of large, comprehensive data …
