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
The CDC Hemophilia B mutation project mutation list: a new online resource.
Li T et al.
Molecular Genetics & Genomic Medicine, 2013
24498619 (PubMed )
Supplement: mgg30001-0238-SD1.xlsx › CHBMP_Mutation_List
Successful treatment of an injury bleeding on a patient suffering from mild von Willebrand's disease and predisposition to allergic diseases, with recombinant factor VIIA.
Alesci S et al.
Haemophilia : the Official Journal of the World Federation of Hemophilia, 2011
Identification of novel and recurrent mutations in Tunisian haemophilia B patients.
Elmahmoudi H et al.
Haemophilia : the Official Journal of the World Federation of Hemophilia, 2011
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