RT Journal Article
SR Electronic
T1 TCRex: a webtool for the prediction of T-cell receptor sequence epitope specificity
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 373472
DO 10.1101/373472
A1 Sofie Gielis
A1 Pieter Moris
A1 Nicolas De Neuter
A1 Wout Bittremieux
A1 Benson Ogunjimi
A1 Kris Laukens
A1 Pieter Meysman
YR 2018
UL http://biorxiv.org/content/early/2018/07/22/373472.abstract
AB Identification of T-cell receptor (TCR) repertoire epitope targets constitutes an important part of many TCR repertoire studies. To date, we are still relying on time consuming epitope binding experiments for the identification of epitope-specific TCR sequences. Recently, we showed that the prediction of epitope-TCR interaction is possible using a random forest model. We implemented this method in a webtool called TCRex. TCRex is the first tool that enables the prediction of TCR-epitope recognition. It allows users to upload TCR sequences and predict interaction with multiple known cancer or viral epitopes or train new prediction models for new epitopes. TCRex is freely available for academic use at tcrex.biodatamining.be