AIMC Topic: Antigens, Neoplasm

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NeoaPred: a deep-learning framework for predicting immunogenic neoantigen based on surface and structural features of peptide-human leukocyte antigen complexes.

Bioinformatics (Oxford, England) Sep 2, 2024
MOTIVATION: Neoantigens, derived from somatic mutations in cancer cells, can elicit anti-tumor immune responses when presented to autologous T cells by human leukocyte antigen. Identifying immunogenic neoantigens is crucial for cancer immunotherapy d...
Humans Software Neoplasms Peptides Deep Learning Computational Biology Antigens, Neoplasm HLA Antigens Histocompatibility Antigens Class I
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DeepHLApan: A Deep Learning Approach for the Prediction of Peptide-HLA Binding and Immunogenicity.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2024
Neoantigens are crucial in distinguishing cancer cells from normal ones and play a significant role in cancer immunotherapy. The field of bioinformatics prediction for tumor neoantigens has rapidly developed, focusing on the prediction of peptide-HLA...
Humans Software Neoplasms Peptides Deep Learning Protein Binding Computational Biology Antigens, Neoplasm HLA Antigens
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Treatment Potential for Macular Cone Vision in Leber Congenital Amaurosis Due to CEP290 or NPHP5 Mutations: Predictions From Artificial Intelligence.

Investigative ophthalmology & visual science Jun 3, 2019
PURPOSE: To use supervised machine learning to predict visual function from retinal structure in retinitis pigmentosa (RP) and apply these estimates to CEP290- and NPHP5-associated Leber congenital amaurosis (LCA) to determine the potential for funct...
Humans Machine Learning Female Young Adult Adult Male Middle Aged Adolescent Antigens, Neoplasm Neoplasm Proteins Tomography, Optical Coherence Mutation Visual Fields Visual Field Tests Cytoskeletal Proteins Genetic Therapy Cell Cycle Proteins Color Vision Defects Retinal Cone Photoreceptor Cells Calmodulin-Binding Proteins Leber Congenital Amaurosis Retinitis Pigmentosa
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Highly sensitive detection of human cancer antigens by an immunogold-silver assay chip coupled with a polythiophene-based optical sensor.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
This work presents a novel method for protein or cancer antigen detection in clinical samples by an immunogold-silver assay microfluidic biochip coupled with a polythiophene-based organic photodetector. The method has showed a detection limit below 1...
Humans Neoplasms Biosensing Techniques Antigens, Neoplasm Limit of Detection Silver Microfluidics Immunohistochemistry
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