AIMC Topic: Loss of Function Mutation

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Mapping variants in thyroid hormone transporter MCT8 to disease severity by genomic, phenotypic, functional, structural and deep learning integration.

Nature communications Mar 12, 2025
Predicting and quantifying phenotypic consequences of genetic variants in rare disorders is a major challenge, particularly pertinent for 'actionable' genes such as thyroid hormone transporter MCT8 (encoded by the X-linked SLC16A2 gene), where loss-o...
Humans Phenotype Female Male Deep Learning Genomics Thyroid Hormones Loss of Function Mutation Muscular Atrophy Muscle Hypotonia Monocarboxylic Acid Transporters Symporters X-Linked Intellectual Disability
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DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier.

PLoS computational biology Nov 18, 2020
Predicting the phenotypes resulting from molecular perturbations is one of the key challenges in genetics. Both forward and reverse genetic screen are employed to identify the molecular mechanisms underlying phenotypes and disease, and these resulted...
Humans Neural Networks, Computer Phenotype Animals Deep Learning Genetic Predisposition to Disease Genetic Association Studies Computational Biology Databases, Genetic Gene Ontology Loss of Function Mutation
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When loss-of-function is loss of function: assessing mutational signatures and impact of loss-of-function genetic variants.

Bioinformatics (Oxford, England) Jul 15, 2017
MOTIVATION: Loss-of-function genetic variants are frequently associated with severe clinical phenotypes, yet many are present in the genomes of healthy individuals. The available methods to assess the impact of these variants rely primarily upon evol...
Humans Machine Learning Software Computational Biology Proteins Protein Conformation Sequence Analysis, Protein Loss of Function Mutation
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