AIMC Topic: Alleles

Clear Filters Showing 21 to 30 of 71 articles

Interpretation of allele-specific chromatin accessibility using cell state-aware deep learning.

Genome research
Genomic sequence variation within enhancers and promoters can have a significant impact on the cellular state and phenotype. However, sifting through the millions of candidate variants in a personal genome or a cancer genome, to identify those that i...

Deep learning pan-specific model for interpretable MHC-I peptide binding prediction with improved attention mechanism.

Proteins
Accurate prediction of peptide binding affinity to the major histocompatibility complex (MHC) proteins has the potential to design better therapeutic vaccines. Previous work has shown that pan-specific prediction algorithms can achieve better predict...

A deep learning method for HLA imputation and trans-ethnic MHC fine-mapping of type 1 diabetes.

Nature communications
Conventional human leukocyte antigen (HLA) imputation methods drop their performance for infrequent alleles, which is one of the factors that reduce the reliability of trans-ethnic major histocompatibility complex (MHC) fine-mapping due to inter-ethn...

Creating artificial human genomes using generative neural networks.

PLoS genetics
Generative models have shown breakthroughs in a wide spectrum of domains due to recent advancements in machine learning algorithms and increased computational power. Despite these impressive achievements, the ability of generative models to create re...

Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2 leading to universal blueprints for vaccine designs.

Scientific reports
The global population is at present suffering from a pandemic of Coronavirus disease 2019 (COVID-19), caused by the novel coronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The goal of this study was to use artificial intellige...

Identification and validation of 174 COVID-19 vaccine candidate epitopes reveals low performance of common epitope prediction tools.

Scientific reports
The outbreak of SARS-CoV-2 (2019-nCoV) virus has highlighted the need for fast and efficacious vaccine development. Stimulation of a proper immune response that leads to protection is highly dependent on presentation of epitopes to circulating T-cell...

Transfer learning enables prediction of CYP2D6 haplotype function.

PLoS computational biology
Cytochrome P450 2D6 (CYP2D6) is a highly polymorphic gene whose protein product metabolizes more than 20% of clinically used drugs. Genetic variations in CYP2D6 are responsible for interindividual heterogeneity in drug response that can lead to drug ...

Machine learning discriminates a movement disorder in a zebrafish model of Parkinson's disease.

Disease models & mechanisms
Animal models of human disease provide an system that can reveal molecular mechanisms by which mutations cause pathology, and, moreover, have the potential to provide a valuable tool for drug development. Here, we have developed a zebrafish model of...

Evaluating the informativeness of deep learning annotations for human complex diseases.

Nature communications
Deep learning models have shown great promise in predicting regulatory effects from DNA sequence, but their informativeness for human complex diseases is not fully understood. Here, we evaluate genome-wide SNP annotations from two previous deep learn...

Unsupervised Clustering of Missense Variants in HNF1A Using Multidimensional Functional Data Aids Clinical Interpretation.

American journal of human genetics
Exome sequencing in diabetes presents a diagnostic challenge because depending on frequency, functional impact, and genomic and environmental contexts, HNF1A variants can cause maturity-onset diabetes of the young (MODY), increase type 2 diabetes ris...