Associated Papers
Integrating evidence from protein domains to identify cancer driver mutations.
Ostroverkhova D et al.
Protein Science : a Publication of the Protein Society, 2026
41556616 (PubMed )
Supplement: PRO-35-e70422-s002.xlsx › Table_S1
Integrating epidemiology and genomics data to estimate the prevalence of acquired cysteine drug targets in the U.S. cancer patient population.
Arun AS et al.
The Pharmacogenomics Journal, 2025
40044654 (PubMed )
Supplement: 41397_2025_364_MOESM3_ESM.xlsx › Sheet1
Identification of T Cell Receptors Targeting a Neoantigen Derived from Recurrently Mutated FGFR3.
Tate T et al.
Cancers, 2023
36831375 (PubMed )
Supplement: cancers-15-01031-s001.zip › Supplementary_Table_S1.xlsx › Table_S1
A Comprehensive Analysis of Cutaneous Melanoma Patients in Greece Based on Multi-Omic Data.
Kontogianni G et al.
Cancers, 2023
36765773 (PubMed )
Supplement: cancers-15-00815-s001.zip › Tables_S1-S7.xlsx › Supplementary_Table_1
Comprehensive Characterization of the Coding and Non-Coding Single Nucleotide Polymorphisms in the Tumor Protein p63 (TP63) Gene Using In Silico Tools.
Akter S et al.
Biomolecules, 2021
Analysis of CRISPR-Cas9 screens identifies genetic dependencies in melanoma.
Christodoulou E et al.
Pigment Cell & Melanoma Research, 2021
32767816 (PubMed )
Supplement: PCMR-34-122-s006.xlsx › Sheet1
A risk-associated Active transcriptome phenotype expressed by histologically normal human breast tissue and linked to a pro-tumorigenic adipocyte population.
Kang T et al.
Breast Cancer Research : Bcr, 2020
32736587 (PubMed )
Supplement: 13058_2020_1322_MOESM3_ESM.xlsx › All_Calls
Diversity spectrum analysis identifies mutation-specific effects of cancer driver genes.
Dong X et al.
Communications Biology, 2020
31925297 (PubMed )
Supplement: 42003_2019_736_MOESM10_ESM.xlsx › Sheet1
Analysis of error profiles in deep next-generation sequencing data.
Ma X et al.
Genome Biology, 2019
30867008 (PubMed )
Supplement: 13059_2019_1659_MOESM1_ESM.xlsx › S3_b
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