Predicting functional effects of missense variants in voltage-gated sodium and calcium channels

Henrike Heyne(Broad Institute), David Báez-Nieto(Broad Institute), Sumaiya Iqbal(Broad Institute), Duncan S. Palmer(Broad Institute), Andreas Brunklaus(Royal Hospital for Children), Patrick May(University of Luxembourg), Epi25 Collaborative(University of Southern Denmark), Katrine M. Johannesen(University of Southern Denmark), Stephan Lauxmann(Hertie Institute for Clinical Brain Research), Johannes R. Lemke(University of Southern Denmark), Rikke S. Møller(Cleveland Clinic), Eduardo Pérez‐Palma(Cleveland Clinic), Ute I. Scholl(Heidelberg University), Steffen Syrbe(Heidelberg University), Holger Lerche(Broad Institute), Dennis Lal(Broad Institute), Arthur J. Campbell(Broad Institute), Hao‐Ran Wang(Broad Institute), Jen Q. Pan(Broad Institute), Mark J. Daly(Broad Institute)
Science Translational Medicine
August 12, 2020
Cited by 142Open Access
Full Text

Abstract

A machine learning method can predict loss- versus gain-of-function effects of human genetic variants in disease-associated ion channels.


Related Papers

No related papers found

Powered by citation graph analysis