tcr repertoire importance for medical treatments

The peptides derived from those pathogens provide information to T cells when they are presented on the major histocompatibility complex (MHC) as antigens.

Among the different types of immune cells, T cells play various roles in the recognition, memory, and eviction of such threats ( 1). The immune system is central to maintaining our body in a healthy state by detecting and evicting those pathogens. Our bodies are constantly exposed to threats from various pathogenic bacteria, viruses, and cancer cells. In this paper, we review recent repertoire analysis methods based on machine learning and deep learning and discuss their prospects. Of various topics in immunology, T cell receptor repertoire analysis is one of the most important targets of machine learning for assessing the state and abnormalities of immune systems. Various data and database platforms are now driving the rapid progress of machine learning for immunological data analysis.

Sparked by the development of genome sequencing technology, the quantity and quality of data handled in immunological research have been changing dramatically. 5Institute of Industrial Science, The University of Tokyo, Tokyo, Japan.4Graduate School of Medical Life Science, Yokohama City University, Yokohama, Japan.3Laboratory for Immune Homeostasis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.2National Research Institute of Police Science, Kashiwa, Chiba, Japan.1Graduate School of Engineering, The University of Tokyo, Tokyo, Japan.Yotaro Katayama 1* Ryo Yokota 2 Taishin Akiyama 3,4 Tetsuya J.

Tcr repertoire importance for medical treatments