Associated Papers
A Machine Learning Framework Predicts the Clinical Severity of Hemophilia B Caused by Point-Mutations.
Lopes TJS et al.
Frontiers in Bioinformatics, 2022
36304295 (PubMed )
Supplement: DataSheet1.zip › Supplementary_Table_5_-_Disambiguate.xlsx › Predictions
Splicing dysregulation contributes to the pathogenicity of several F9 exonic point variants.
Katneni UK et al.
Molecular Genetics & Genomic Medicine, 2019
31257730 (PubMed )
Supplement: MGG3-7-e840-s002.xls › F9_Splicing_Data
An interactive mutation database for human coagulation factor IX provides novel insights into the phenotypes and genetics of hemophilia B.
Rallapalli PM et al.
Journal of Thrombosis and Haemostasis : Jth, 2013
Identification of mutations in the F9 gene including exon deletion by multiplex ligation-dependent probe amplification in 33 unrelated Korean patients with haemophilia B.
Kwon MJ et al.
Haemophilia : the Official Journal of the World Federation of Hemophilia, 2008
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