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In Vitro Tumor Cell Rechallenge For Predictive Evaluation of Chimeric Antigen Receptor T Cell Antitumor Function
Published on: February 27, 2019
Pep2TCR: Accurate prediction of CD4 T cell receptor binding specificity through transfer learning and ensemble
Kaixuan Diao1,2,3, Tao Wu1, Xiangyu Zhao1
1School of Life Science and Technology ShanghaiTech University Shanghai China.
None:
Pep2TCR is an advanced deep learning model designed to predict cluster of differentiation 4 (CD4) T cell receptor (TCR) binding specificity, addressing the challenge posed by limited CD4 TCR data. It shows marked improvement over existing models. Pep2TCR is accessible via a user-friendly website for predicting CD4 TCR specificity at http://pep2tcr.liuxslab.com. This innovative tool holds promise for advancing personalized cancer immunotherapies.
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