Associated Papers
Precision in prediction: tailoring machine learning models for breast cancer missense variants pathogenicity prediction.
Ahmad RM et al.
Briefings in Bioinformatics, 2025
41263939 (PubMed )
Supplement: supplementary_materials_bbaf611_1_.zip › Supplementary_materials_bbaf611 › Supplementary_Table_S8.xlsx › Sheet1
Germline predisposition in multiple myeloma.
Martins Rodrigues F et al.
Iscience, 2025
39845416 (PubMed )
Supplement: mmc3.xlsx › S2H.Vars_clinic_WES_Family
vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines.
Munté E et al.
Bioinformatics (oxford, England), 2023
36916756 (PubMed )
Supplement: btad128_supplementary_data.zip › btad128_Supplementary_Data › Supplementary_tables10022023.xlsx › ST8-CDH1
Evaluation of AlphaFold structure-based protein stability prediction on missense variations in cancer.
Keskin Karakoyun H et al.
Frontiers in Genetics, 2023
36896237 (PubMed )
Supplement: Table1.xlsx › clinvar_breastcancer_allvariant
PhenoHM: human-mouse comparative phenome-genome server.
Sardana D et al.
Nucleic Acids Research, 2010
20507906 (PubMed )
Supplement: gkq472_nar-00429-web-b-2010-File006.xls › MPO_to_OMIM_allelic_Variants
Dysregulation of the E-cadherin/catenin complex by irreversible mutations in human carcinomas.
Berx G et al.
Cell Adhesion and Communication, 1998
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