An Artificial Intelligence Model for Profiling the Landscape of Antigen-binding Affinities of Massive BCR Sequencing Data.

Bing SongKaiwen WangSaiyang NaJia YaoFarjana J FattahMitchell S von ItzsteinDonghan M YangJialiang LiuYaming XueChaoying LiangYuzhi GuoIndu RamanChengsong ZhuJonathan E DowellJade HomsiSawsan RashdanShengjie YangMary E GwinDavid HsiehchenYvonne Gloria-McCutchenPrithvi RajXiaochen BaiJun WangJose Conejo-GarciaYang XieDavid E GerberJunzhou HuangTao Wang

Published in: bioRxiv : the preprint server for biology (2024)

This work introduces Cmai, an Artificial Intelligence tool that predicts antibody-antigen binding with high accuracy from massive sequencing data, which offers a potent means to elucidate the relevance of antigen-antibody interactions in various biomedical contexts and to advance antibody-centric translational development.

Keyphrases

artificial intelligence
big data
single cell
machine learning
deep learning
electronic health record
acute lymphoblastic leukemia
tyrosine kinase