RNA-GPS predicts high-resolution RNA subcellular localization and highlights the role of splicing
Published in RNA, 2020
Recommended citation: Wu, K.E., Parker, K.R., Fazal, F.M., Chang, H.Y. and Zou, J., 2020. RNA-GPS predicts high-resolution RNA subcellular localization and highlights the role of splicing. RNA, 26(7), pp.851-865. Vancouver https://rnajournal.cshlp.org/content/26/7/851.short
The subcellular localization of RNA transcripts within a cell greatly influences the biological role that that transcript plays, and how proteins are subsequenty distributed across the cell. Based on the biological intuition that an RNA transcript is naturally delineated into regions (i.e., 5’ UTR, coding sequence, 3’ UTR), we develop RNA-GPS, a machine learning model predicting subcellular localization of a transcript given its nucleotide sequence.