AIMC Topic: Epitopes

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Semi-supervised learning for somatic variant calling and peptide identification in personalized cancer immunotherapy.

BMC bioinformatics
BACKGROUND: Personalized cancer vaccines are emerging as one of the most promising approaches to immunotherapy of advanced cancers. However, only a small proportion of the neoepitopes generated by somatic DNA mutations in cancer cells lead to tumor r...

Machine learning-guided evolution of BMP-2 knuckle Epitope-Derived osteogenic peptides to target BMP receptor II.

Journal of drug targeting
Bone morphogenetic protein-2 (BMP-2) is a key regulator of bone formation, growth and regeneration, which contains a conformational wrist epitope and a linear knuckle epitope that are functionally responsible for the protein by mediating its interact...

A novel algorithm to improve specificity in ovarian cancer detection.

Cancer treatment and research communications
BACKGROUND: Measurement of autoantibodies (AAbs) to tumor associated antigens has been proposed to aid in the early detection of ovarian cancer with high specificity. Here we describe a multiplex approach to evaluate selected peptide epitopes of p53 ...

Ab-initio conformational epitope structure prediction using genetic algorithm and SVM for vaccine design.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: T-cell epitope structure identification is a significant challenging immunoinformatic problem within epitope-based vaccine design. Epitopes or antigenic peptides are a set of amino acids that bind with the Major Histocompati...

Machine learning reveals a non-canonical mode of peptide binding to MHC class II molecules.

Immunology
MHC class II molecules play a fundamental role in the cellular immune system: they load short peptide fragments derived from extracellular proteins and present them on the cell surface. It is currently thought that the peptide binds lying more or les...

Enhancing the Biological Relevance of Machine Learning Classifiers for Reverse Vaccinology.

International journal of molecular sciences
Reverse vaccinology (RV) is a bioinformatics approach that can predict antigens with protective potential from the protein coding genomes of bacterial pathogens for subunit vaccine design. RV has become firmly established following the development of...

Improved pan-specific prediction of MHC class I peptide binding using a novel receptor clustering data partitioning strategy.

HLA
Pan-specific prediction of receptor-ligand interaction is conventionally done using machine-learning methods that integrates information about both receptor and ligand primary sequences. To achieve optimal performance using machine learning, dealing ...

An ontology for major histocompatibility restriction.

Journal of biomedical semantics
BACKGROUND: MHC molecules are a highly diverse family of proteins that play a key role in cellular immune recognition. Over time, different techniques and terminologies have been developed to identify the specific type(s) of MHC molecule involved in ...