AIMC Topic: Antigens, Neoplasm

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Computational biology and artificial intelligence in mRNA vaccine design for cancer immunotherapy.

Frontiers in cellular and infection microbiology
Messenger RNA (mRNA) vaccines offer an adaptable and scalable platform for cancer immunotherapy, requiring optimal design to elicit a robust and targeted immune response. Recent advancements in bioinformatics and artificial intelligence (AI) have sig...

LRMAHpan: a novel tool for multi-allelic HLA presentation prediction using Resnet-based and LSTM-based neural networks.

Frontiers in immunology
INTRODUCTION: The identification of peptides eluted from HLA complexes by mass spectrometry (MS) can provide critical data for deep learning models of antigen presentation prediction and promote neoantigen vaccine design. A major challenge remains in...

Personalized cancer vaccine design using AI-powered technologies.

Frontiers in immunology
Immunotherapy has ushered in a new era of cancer treatment, yet cancer remains a leading cause of global mortality. Among various therapeutic strategies, cancer vaccines have shown promise by activating the immune system to specifically target cancer...

Cancer Immunotherapies Ignited by a Thorough Machine Learning-Based Selection of Neoantigens.

Advanced biology
Identification of neoantigens, derived from somatic DNA alterations, emerges as a promising strategy for cancer immunotherapies. However, not all somatic mutations result in immunogenicity, hence, efficient tools to predict the immunogenicity of neoe...

Machine learning for the identification of neoantigen-reactive CD8 + T cells in gastrointestinal cancer using single-cell sequencing.

British journal of cancer
BACKGROUND: It appears that tumour-infiltrating neoantigen-reactive CD8 + T (Neo T) cells are the primary driver of immune responses to gastrointestinal cancer in patients. However, the conventional method is very time-consuming and complex for ident...

Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy.

Frontiers in immunology
Cancer immunotherapy has witnessed rapid advancement in recent years, with a particular focus on neoantigens as promising targets for personalized treatments. The convergence of immunogenomics, bioinformatics, and artificial intelligence (AI) has pro...

Sa-TTCA: An SVM-based approach for tumor T-cell antigen classification using features extracted from biological sequencing and natural language processing.

Computers in biology and medicine
Accurately predicting tumor T-cell antigen (TTCA) sequences is a crucial task in the development of cancer vaccines and immunotherapies. TTCAs derived from tumor cells, are presented to immune cells (T cells) through major histocompatibility complex ...

GraphMHC: Neoantigen prediction model applying the graph neural network to molecular structure.

PloS one
Neoantigens are tumor-derived peptides and are biomarkers that can predict prognosis related to immune checkpoint inhibition by estimating their binding to major histocompatibility complex (MHC) proteins. Although deep neural networks have been prima...

CanVaxKB: a web-based cancer vaccine knowledgebase.

NAR cancer
Cancer vaccines have been increasingly studied and developed to prevent or treat various types of cancers. To systematically survey and analyze different reported cancer vaccines, we developed CanVaxKB (https://violinet.org/canvaxkb), the first web-b...

A facile approach to preparing personalized cancer vaccines using iron-based metal organic framework.

Frontiers in immunology
BACKGROUND: Considering the diversity of tumors, it is of great significance to develop a simple, effective, and low-cost method to prepare personalized cancer vaccines.