Explainable machine learning for profiling the immunological synapse and functional characterization of therapeutic antibodies.

ABSTRACT: Therapeutic antibodies are widely used to treat severe diseases. Most of them alter immune cells and act within the immunological synapse; an essential cell-to-cell interaction to direct the humoral immune response. Although many antibody designs are generated and evaluated, a high-throughput tool for systematic antibody characterization and prediction of function is lacking. Here, we introduce the first comprehensive open-source framework, scifAI (single-cell imaging flow cytometry AI), for preprocessing, feature engineering, and explainable, predictive machine learning on imaging flow cytometry (IFC) data. Additionally, we generate the largest publicly available IFC dataset of the human immunological synapse containing over 2.8 million images. Using scifAI, we analyze class frequency and

SUBMITTER: Shetab Boushehri S 

PROVIDER: S-EPMC10689847 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature