Cargando…
Predicting functional effects of ion channel variants using new phenotypic machine learning methods
Missense variants in genes encoding ion channels are associated with a spectrum of severe diseases. Variant effects on biophysical function correlate with clinical features and can be categorized as gain- or loss-of-function. This information enables a timely diagnosis, facilitates precision therapy...
Autores principales: | Boßelmann, Christian Malte, Hedrich, Ulrike B. S., Lerche, Holger, Pfeifer, Nico |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10019634/ https://www.ncbi.nlm.nih.gov/pubmed/36877742 http://dx.doi.org/10.1371/journal.pcbi.1010959 |
Ejemplares similares
-
Predicting the functional effects of voltage-gated potassium channel missense variants with multi-task learning
por: Boßelmann, Christian Malte, et al.
Publicado: (2022) -
Therapeutic Potential of Sodium Channel Blockers as a Targeted Therapy Approach in KCNA1-Associated Episodic Ataxia and a Comprehensive Review of the Literature
por: Lauxmann, Stephan, et al.
Publicado: (2021) -
Briefing in Application of Machine Learning Methods in Ion Channel Prediction
por: Lin, Hao, et al.
Publicado: (2015) -
Dravet Variant SCN1A(A1783V) Impairs Interneuron Firing Predominantly by Altered Channel Activation
por: Layer, Nikolas, et al.
Publicado: (2021) -
Predicting Ion Channels Genes and Their Types With Machine Learning Techniques
por: Han, Ke, et al.
Publicado: (2019)