Binding of short antigenic peptides to major histocompatibility complex (MHC) molecules is
a core step in adaptive immune response. Precise identification of MHC-restricted peptides …

Predicting drug side effects is a critical task in the drug discovery, which attracts great
attentions in both academy and industry. Although lots of machine learning methods have …

Pneumonic plague is a highly virulent infectious disease with 100% mortality rate, and its
causative organism Yersinia pestis poses a serious threat for deliberate use as a bioterror …

Motivation Computationally predicting major histocompatibility complex (MHC)-peptide
binding affinity is an important problem in immunological bioinformatics. Recent cutting …

Klebsiella pneumoniae is a hospital-acquired pathogen that leads to various infections.
There is a great interest in developing an efficient Klebsiella vaccine and epitope-based …

The ability to track CD4 T cells elicited in response to pathogen infection or vaccination is
critical because of the role these cells play in protective immunity. Coupled with advances in …

Autoantibodies that target the water channel aquaporin-4 (AQP4) in neuromyelitis optica
(NMO) are IgG1, a T cell-dependent Ig subclass. However, a role for AQP4-specific T cells in …

The prediction of major histocompatibility complex (MHC)-peptide binding affinity is an
important branch in immune bioinformatics, especially helpful in accelerating the design of …

The immune system has evolved to make a diverse repertoire of peptides processed from
self and foreign proteomes, which are displayed in antigen-binding grooves of major …

Background Computational prediction of major histocompatibility complex class II (MHC-II)
binding peptides can assist researchers in understanding the mechanism of immune …