Transite: A Computational Motif-Based Analysis Platform That Identifies RNA-Binding Proteins Modulating Changes in Gene Expression
Name
1-s2.0-S2211124720310494-main.pdf
Description
Published version
Size
17.19 MB
Format
Unknown
Checksum (MD5)
c57833690ca5a3d3e952d6e283a0bfc8
Author(s)
Krismer, Konstantin
Bird, Molly A.
Varmeh, Shohreh
Handly, Erika D.
Gattinger, Anna
Bernwinkler, Thomas
Anderson, Daniel A.
Heinzel, Andreas
Joughin, Brian A.
Kong, Yi Wen
Date Issued
August 2020
Journal
Cell Reports
Publisher
Elsevier BV
Version
Final published version
Abstract
© 2020 The Author(s) Krismer et al. present a computational approach to identify RNA-binding proteins (RBPs) that modulate post-transcriptional control of gene expression using RNA expression data as inputs. By applying this approach to publicly available patient datasets, they identify and experimentally confirm that the RBP hnRNPC contributes to chemotherapy resistance in lung cancer.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Center for Precision Cancer Medicine
Koch Institute for Integrative Cancer Research at MIT
Massachusetts Institute of Technology. Synthetic Biology Center
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Biology
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.celrep.2020.108064
