Associated Papers
Reannotation of cancer mutations based on expressed RNA transcripts reveals functional non-coding mutations in melanoma.
Pepe D et al.
American Journal of Human Genetics, 2025
40359938 (PubMed )
Supplement: mmc6.xlsx › Sheet_1
Comprehensive structure-function analysis reveals gain- and loss-of-function mechanisms impacting oncogenic KRAS activity.
Kwon JJ et al.
Biorxiv : the Preprint Server for Biology, 2024
39484452 (PubMed )
Supplement: media-2.zip › Extended_Data_Tables › Extended_Data_Table_1.xlsx › KRAS_GOF_DMS_Screen
The fork remodeler helicase-like transcription factor in cancer development: all at once.
Waheed Y et al.
Biochimica Et Biophysica Acta. Molecular Basis of Disease, 2024
KRAS Mutation Subtypes and Their Association with Other Driver Mutations in Oncogenic Pathways.
Mondal K et al.
Cells, 2024
Prognosis and Characterization of Microenvironment in Cervical Cancer Influenced by Fatty Acid Metabolism-Related Genes.
Zhou Y et al.
Journal of Oncology, 2023
36936374 (PubMed )
Supplement: 6851036.f1.zip › supplementary_figure_1-23__1_.pdf
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
Spatially interacting phosphorylation sites and mutations in cancer.
Huang KL et al.
Nature Communications, 2021
33875650 (PubMed )
Supplement: 41467_2021_22481_MOESM4_ESM.xlsx › TableS5.ActMutationClusters
Transitioning the Molecular Tumor Board from Proof of Concept to Clinical Routine: A German Single-Center Analysis.
Hoefflin R et al.
Cancers, 2021
33800365 (PubMed )
Supplement: cancers-13-01151-s001.zip › Supplementary_Data_1.xlsx › S_Data_1
Integrative omics analyses broaden treatment targets in human cancer.
Sengupta S et al.
Genome Medicine, 2018
30053901 (PubMed )
Supplement: 13073_2018_564_MOESM2_ESM.xlsx › 13
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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