AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Epitopes

Showing 41 to 50 of 50 articles

Clear Filters

High-order neural networks and kernel methods for peptide-MHC binding prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Effective computational methods for peptide-protein binding prediction can greatly help clinical peptide vaccine search and design. However, previous computational methods fail to capture key nonlinear high-order dependencies between diff...

Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification.

Immunogenetics
A key event in the generation of a cellular response against malicious organisms through the endocytic pathway is binding of peptidic antigens by major histocompatibility complex class II (MHC class II) molecules. The bound peptide is then presented ...

Gapped sequence alignment using artificial neural networks: application to the MHC class I system.

Bioinformatics (Oxford, England)
MOTIVATION: Many biological processes are guided by receptor interactions with linear ligands of variable length. One such receptor is the MHC class I molecule. The length preferences vary depending on the MHC allele, but are generally limited to pep...

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 ...

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 ...

Better living through ontologies at the Immune Epitope Database.

Database : the journal of biological databases and curation
UNLABELLED: The Immune Epitope Database (IEDB) project incorporates independently developed ontologies and controlled vocabularies into its curation and search interface. This simplifies curation practices, improves the user query experience and faci...

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...

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...

HLA class I binding prediction via convolutional neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Many biological processes are governed by protein-ligand interactions. One such example is the recognition of self and non-self cells by the immune system. This immune response process is regulated by the major histocompatibility complex ...