Associated Papers
Familial colorectal cancer: search for novel predisposition genes.
Försti A et al.
Human Genomics, 2025
Mapping the Functional Landscape of KCNQ1 to Define Ion Channel Mechanisms and Arrhythmia Risk.
Harvey ML et al.
Medrxiv : the Preprint Server for Health Sciences, 2025
Predicting the Damaging Potential of Uncharacterized KCNQ1 and KCNE1 Variants.
Tarnovskaya SI et al.
International Journal of Molecular Sciences, 2025
Integrative analysis of KCNQ1 variants reveals molecular mechanisms of type 1 long QT syndrome pathogenesis.
Brewer KR et al.
Proceedings of the National Academy of Sciences of the United States of America, 2025
High-throughput functional mapping of variants in an arrhythmia gene, KCNE1, reveals novel biology.
Muhammad A et al.
Genome Medicine, 2024
Cardiac arrhythmia and epilepsy genetic variants in sudden unexpected death in epilepsy.
Aschner A et al.
Frontiers in Neurology, 2024
Predicting the functional impact of KCNQ1 variants with artificial neural networks.
Phul S et al.
Plos Computational Biology, 2022
Evolutionary coupling analysis guides identification of mistrafficking-sensitive variants in cardiac K+ channels: Validation with hERG.
Zhang Y et al.
Frontiers in Pharmacology, 2022
A computational model of induced pluripotent stem-cell derived cardiomyocytes for high throughput risk stratification of KCNQ1 genetic variants.
Kernik DC et al.
Plos Computational Biology, 2020
Identification of putative pathogenic single nucleotide variants (SNVs) in genes associated with heart disease in 290 cases of stillbirth.
Sahlin E et al.
Plos One, 2019
Using the genome aggregation database, computational pathogenicity prediction tools, and patch clamp heterologous expression studies to demote previously published long QT syndrome type 1 mutations from pathogenic to benign.
Clemens DJ et al.
Heart Rhythm, 2018
Mechanisms of KCNQ1 channel dysfunction in long QT syndrome involving voltage sensor domain mutations.
Huang H et al.
Science Advances, 2018
Predicting the Functional Impact of KCNQ1 Variants of Unknown Significance.
Li B et al.
Circulation. Cardiovascular Genetics, 2017
Assessment of the predictive accuracy of five in silico prediction tools, alone or in combination, and two metaservers to classify long QT syndrome gene mutations.
Leong IU et al.
Bmc Medical Genetics, 2015
The genetic component of Brugada syndrome.
Nielsen MW et al.
Frontiers in Physiology, 2013
Overlapping LQT1 and LQT2 phenotype in a patient with long QT syndrome associated with loss-of-function variations in KCNQ1 and KCNH2.
Cordeiro JM et al.
Canadian Journal of Physiology and Pharmacology, 2010
Compound mutations in a patient with congenital long QT syndrome: Clinical challenges and genetic interpretation.
Fukumoto H et al.
Pediatrics International : Official Journal of the Japan Pediatric Society, 0