AIMC Topic: Mutation, Missense

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Accurate Prediction of Transcriptional Activity of Single Missense Variants in HIV Tat with Deep Learning.

International journal of molecular sciences Mar 24, 2023
Tat is an essential gene for increasing the transcription of all HIV genes, and affects HIV replication, HIV exit from latency, and AIDS progression. The Tat gene frequently mutates in vivo and produces variants with diverse activities, contributing ...
Transcription, Genetic Mutation, Missense tat Gene Products, Human Immunodeficiency Virus Transcriptional Activation Humans Deep Learning Acquired Immunodeficiency Syndrome
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Clinical feature-related single-base substitution sequence signatures identified with an unsupervised machine learning approach.

BMC medical genomics Dec 20, 2021
BACKGROUND: Mutation processes leave different signatures in genes. For single-base substitutions, previous studies have suggested that mutation signatures are not only reflected in mutation bases but also in neighboring bases. However, because of th...
Algorithms Cluster Analysis Unsupervised Machine Learning Mutation Mutation, Missense Humans
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Predicting deleterious missense genetic variants via integrative supervised nonnegative matrix tri-factorization.

Scientific reports Dec 9, 2021
Among an assortment of genetic variations, Missense are major ones which a small subset of them may led to the upset of the protein function and ultimately end in human diseases. Various machine learning methods were declared to differentiate deleter...
Computational Biology Systems Biology Supervised Machine Learning Mutation, Missense Reproducibility of Results ROC Curve Genetic Association Studies Humans Algorithms
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PremPLI: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions.

Communications biology Nov 19, 2021
Resistance to small-molecule drugs is the main cause of the failure of therapeutic drugs in clinical practice. Missense mutations altering the binding of ligands to proteins are one of the critical mechanisms that result in genetic disease and drug r...
Proteins Ligands Mutation, Missense Machine Learning Protein Binding
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Machine learning-based identification and characterization of 15 novel pathogenic SUOX missense mutations.

Molecular genetics and metabolism Aug 8, 2021
Isolated sulfite oxidase deficiency (ISOD) is a rare hereditary metabolic disease caused by absence of functional sulfite oxidase (SO) due to mutations of the SUOX gene. SO oxidizes toxic sulfite and sulfite accumulation is associated with neurologic...
Humans Machine Learning Genetic Variation Gene Frequency Brain Mutation, Missense Infant, Newborn Genome Oxidoreductases Acting on Sulfur Group Donors Databases, Genetic
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MVP predicts the pathogenicity of missense variants by deep learning.

Nature communications Jan 21, 2021
Accurate pathogenicity prediction of missense variants is critically important in genetic studies and clinical diagnosis. Previously published prediction methods have facilitated the interpretation of missense variants but have limited performance. H...
Heart Defects, Congenital Mutation, Missense Deep Learning Genetic Predisposition to Disease Computational Biology Humans Algorithms Sensitivity and Specificity Neoplasms Autism Spectrum Disorder Reproducibility of Results
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Prediction of rifampicin resistance beyond the RRDR using structure-based machine learning approaches.

Scientific reports Oct 22, 2020
Rifampicin resistance is a major therapeutic challenge, particularly in tuberculosis, leprosy, P. aeruginosa and S. aureus infections, where it develops via missense mutations in gene rpoB. Previously we have highlighted that these mutations reduce p...
Mycobacterium leprae Rifampin Mutation, Missense Leprosy Tuberculosis Staphylococcal Infections Mycobacterium tuberculosis Humans Machine Learning Bacterial Proteins Antitubercular Agents Drug Resistance, Bacterial Staphylococcus aureus
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Unsupervised Clustering of Missense Variants in HNF1A Using Multidimensional Functional Data Aids Clinical Interpretation.

American journal of human genetics Sep 9, 2020
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...
Child Diabetes Mellitus, Type 2 Genetic Predisposition to Disease Unsupervised Machine Learning Principal Component Analysis Mutation, Missense Young Adult Humans Cluster Analysis Adult Datasets as Topic Phenotype Hepatocyte Nuclear Factor 1-alpha Norway Male Gene Expression Female United Kingdom Exome Sequencing Adolescent Registries Alleles
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LEAP: Using machine learning to support variant classification in a clinical setting.

Human mutation Apr 1, 2020
Advances in genome sequencing have led to a tremendous increase in the discovery of novel missense variants, but evidence for determining clinical significance can be limited or conflicting. Here, we present Learning from Evidence to Assess Pathogeni...
Humans Models, Genetic Machine Learning Models, Statistical Cardiovascular Diseases Area Under Curve Neoplasms Mutation, Missense ROC Curve Genomics Logistic Models
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High-Throughput Prediction of MHC Class I and II Neoantigens with MHCnuggets.

Cancer immunology research Dec 23, 2019
Computational prediction of binding between neoantigen peptides and major histocompatibility complex (MHC) proteins can be used to predict patient response to cancer immunotherapy. Current neoantigen predictors focus on estimation of MHC binding aff...
Data Mining Mutation, Missense Histocompatibility Antigens Class II Protein Binding Computational Biology Cancer Vaccines Predictive Value of Tests Histocompatibility Antigens Class I Antigens, Neoplasm CD8-Positive T-Lymphocytes Software Algorithms Neoplasms Humans Neural Networks, Computer Artificial Intelligence
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