Associated Papers
Functional Analysis of Rare RAS Variants of Unknown Significance.
Park S et al.
Cancer Research Communications, 2025
40970755 (PubMed )
Supplement: crc-25-0188_supplementary_table_s5_suppst5.xlsx › Supplementary_Table_S5
Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification.
Padigepati SR et al.
Human Genetics, 2024
39085601 (PubMed )
Supplement: 439_2024_2691_MOESM2_ESM.xlsx › HRAS
Predicting Deleterious Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) of HRAS Gene and In Silico Evaluation of Their Structural and Functional Consequences towards Diagnosis and Prognosis of Cancer.
Chai CY et al.
Biology, 2022
Structural bioinformatics enhances mechanistic interpretation of genomic variation, demonstrated through the analyses of 935 distinct RAS family mutations.
Tripathi S et al.
Bioinformatics (oxford, England), 2021
33226070 (PubMed )
Supplement: btaa972_supplementary_data.zip › RAS_Manuscript_RMarkdown.tar.gz › RAS_Manuscript1.Revised › RAS_Variants_Scores.xlsx › Sheet1
Personalized cancer therapy prioritization based on driver alteration co-occurrence patterns.
Mateo L et al.
Genome Medicine, 2020
32907621 (PubMed )
Supplement: 13073_2020_774_MOESM1_ESM.zip › SupplementaryTables › TableS2.xlsx › Biomarkers
LowMACA: exploiting protein family analysis for the identification of rare driver mutations in cancer.
Melloni GE et al.
Bmc Bioinformatics, 2016
26860319 (PubMed )
Supplement: 12859_2016_935_MOESM2_ESM.xlsx › Table_S5
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