PT  - JOURNAL ARTICLE
AU  - Sofie Gielis
AU  - Pieter Moris
AU  - Nicolas De Neuter
AU  - Wout Bittremieux
AU  - Benson Ogunjimi
AU  - Kris Laukens
AU  - Pieter Meysman
TI  - TCRex: a webtool for the prediction of T-cell receptor sequence epitope specificity
AID  - 10.1101/373472
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 373472
4099  - http://biorxiv.org/content/early/2018/07/22/373472.short
4100  - http://biorxiv.org/content/early/2018/07/22/373472.full
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