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Related Concept Videos

B Cell Activation and Differentiation01:24

B Cell Activation and Differentiation

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The adaptive immune response, a sophisticated defense mechanism, relies on the activation and differentiation of B lymphocytes, or B cells. These processes enable our bodies to mount a tailored response against specific pathogens such as bacteria, free virus particles, toxins, and parasites.
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Antigen receptors are essential components of the immune system crucial in defending the body against foreign invaders. These receptors are present on the surface of B and T cells, enabling them to recognize antigens and mount an appropriate immune response.
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T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
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Updated: Feb 24, 2026

T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing
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T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing

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BiGCN Learns B Cell Functional States by Integrating Single-Cell Transcriptomes and BCR Repertoires.

Xiao Liu1,2, Jianghao Huang1,2, Shasha Zhao1,2

  • 1State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Shanghai, China.

Small Methods
|February 23, 2026
PubMed
Summary
This summary is machine-generated.

A new method, BiGCN, integrates B cell transcriptomic and receptor data to reveal hidden B cell states and functions. This advances understanding of immune regulation and diseases like cancer.

Keywords:
BCR distanceB‐cell receptor (BCR)graph convolutional network (GCN)integrated embeddingscRNA‐seq

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Area of Science:

  • Immunology
  • Computational Biology
  • Systems Medicine

Background:

  • B lymphocytes (B cells) are crucial for immune responses and disease.
  • Analyzing B cell diversity is challenging due to separate transcriptomic and B cell receptor (BCR) repertoire analyses.
  • Existing methods struggle to fully integrate these distinct data types for comprehensive B cell characterization.

Purpose of the Study:

  • To develop a novel computational method, BiGCN, for integrated analysis of single-cell transcriptomic and BCR repertoire data.
  • To enable high-fidelity characterization of B cell states and clonal relationships by unifying these modalities.
  • To improve functional annotation and biological insight into B cell populations.

Main Methods:

  • Developed BiGCN, a method utilizing a graph convolutional network (GCN) framework.
  • Integrated paired single-cell RNA sequencing (scRNA-seq) and single-cell BCR sequencing (scBCR-seq) data.
  • Applied BiGCN to diverse datasets including infectious disease, autoimmunity, and cancer.

Main Results:

  • BiGCN significantly outperforms existing methods in data integration, functional annotation, and biological discovery.
  • Successfully recapitulated B cell maturation and immunoglobulin class switching trajectories.
  • Discovered previously unidentified intermediate B cell subtypes and functional states.

Conclusions:

  • BiGCN provides a versatile and robust platform for B cell research.
  • The method enhances the characterization of B cell states and clonal dynamics.
  • BiGCN accelerates discoveries in immunology, cancer biology, and systems medicine.