AIMC Topic: Mutation, Missense

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Cross-protein transfer learning substantially improves disease variant prediction.

Genome biology Aug 7, 2023
BACKGROUND: Genetic variation in the human genome is a major determinant of individual disease risk, but the vast majority of missense variants have unknown etiological effects. Here, we present a robust learning framework for leveraging saturation m...
Humans Machine Learning Mutation Amino Acid Sequence Mutation, Missense Computational Biology Proteome
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Gene-specific machine learning for pathogenicity prediction of rare BRCA1 and BRCA2 missense variants.

Scientific reports Jun 28, 2023
Machine learning-based pathogenicity prediction helps interpret rare missense variants of BRCA1 and BRCA2, which are associated with hereditary cancers. Recent studies have shown that classifiers trained using variants of a specific gene or a set of ...
Mutation, Missense Virulence Gene Frequency Neural Networks, Computer Machine Learning
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Prediction of Kv11.1 potassium channel PAS-domain variants trafficking via machine learning.

Journal of molecular and cellular cardiology May 13, 2023
Congenital long QT syndrome (LQTS) is characterized by a prolonged QT-interval on an electrocardiogram (ECG). An abnormal prolongation in the QT-interval increases the risk for fatal arrhythmias. Genetic variants in several different cardiac ion chan...
Humans Machine Learning Long QT Syndrome Phenotype KCNQ1 Potassium Channel 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 ...
Acquired Immunodeficiency Syndrome Transcription, Genetic Mutation, Missense Humans Deep Learning tat Gene Products, Human Immunodeficiency Virus Transcriptional Activation
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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...
Mutation, Missense Cluster Analysis Unsupervised Machine Learning Mutation Humans Algorithms
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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...
Systems Biology Supervised Machine Learning Mutation, Missense Genetic Association Studies Computational Biology Humans Reproducibility of Results ROC Curve 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...
Machine Learning Ligands Proteins Protein Binding Mutation, Missense
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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 Infant, Newborn Databases, Genetic Brain Mutation, Missense Genetic Variation Genome Oxidoreductases Acting on Sulfur Group Donors Gene Frequency
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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...
Computational Biology Heart Defects, Congenital Mutation, Missense Deep Learning Genetic Predisposition to Disease Humans Algorithms Reproducibility of Results Autism Spectrum Disorder Sensitivity and Specificity Neoplasms
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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...
Bacterial Proteins Leprosy Staphylococcal Infections Antitubercular Agents Mycobacterium leprae Mycobacterium tuberculosis Humans Rifampin Drug Resistance, Bacterial Tuberculosis Mutation, Missense Machine Learning Staphylococcus aureus
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