Explore gene specific cancer data


View OncoMX data across all data sources. This includes data from EDRN, Bgee, BioXpress, Reactome, and BioMuta.

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Statistics at a Glance

View BioXpress Statistics

View BioMuta Statistics

View EDRN Biomarker Statistics

View Bgee Statistics

View Reactome Statistics

View distribution of proteins across resources

View distribution of unique cancer terms across resources


Summary Statistics

View OncoMX data across all data sources. This includes data from EDRN, Bgee, BioXpress, Reactome, and BioMuta.

Normal Expression Filters
Mutation Filters
Biomarker Filters
FDA Biomarker Filters
Differential Expression Filters
    KICH - Kidney Chromophobe  
    LIHC - Liver Hepatocellular Carcinoma  
    READ - Rectum Adenocarcinoma  
    LUAD - Lung Adenocarcinoma  
    LUSC - Lung Squamous Cell Carcinoma  
    COAD - Colon Adenocarcinoma  
    STAD - Stomach Adenocarcinoma  
    PAAD - Pancreatic adenocarcinoma  
    THCA - Thyroid Cancer  
    KIRP - Kidney renal papillary cell carcinoma  
    HNSC - Head and Neck Squamous Cell Carcinoma  
    BRCA - Breast Invasive Carcinoma  
    PRAD - Prostate Adenocarcinoma  
    CESC - Cervical Squamous Cell Carcinoma  
    KIRC - Kidney Renal Clear Cell Carcinoma  
    ESCA - Esophageal Carcinoma  
    UCEC - Uterine Corpus Endometrial Carcinoma  
    BLCA - Bladder Carcinoma  
Gene Symbol UniProtKB/SwissProt AC EDRN Biomarker # BioMuta Mutations # BioXpress Cancers # Reactome Pathways # Bgee Datasets


OncoMX is an integrated cancer mutation and expression resource for exploring cancer biomarkers alongside related experimental data and functional information. OncoMX is a collaboration between the George Washington University (GW), NASA's Jet Propulsion Laboratory (JPL), the Swiss Institute of Bioinformatics (SIB), and the University of Delaware (UD). The core knowledgebase of OncoMX is derived from integrated cancer mutation (BioMuta) and expression (BioXpress) knowledgebases developed at GW. This collection of cancer data is mapped to biomarkers from EDRN and other sources, and augmented by normal expression data from Bgee and custom literature mining for mutation (DiMeX) and expression (DEXTER) software developed at UD. Combining this information is expected to improve functional interpretation of the reported variants, expression profiles, and other evidence of cancer involvement. Resulting data are wrapped into the OncoMX database, mapped to additional functional information and made available through the web portal. Here, a user can explore cancer data from various perspectives: for example, the biomarker vizualization enables a a user to see all attributes related to any biomarker annotations for a gene of interest. All datasets used by OncoMX, as well as additional custom datasets, are made available through the parallel data portal at www.data.oncomx.org.

Our Team

Raja Mazumder Multi-PI, GW
Dan Crichton Multi-PI, JPL
Frédéric Bastian SIB Lead
Vijay Shanker UD Lead
Hayley Dingerdissen GW
Evan Holmes GW
Robel Kahsay GW
Heather Kincaid JPL
Marc Robinson-Rechavi SIB
Stephanie Singleton GW

Additional Photos Coming...

Amanda Bell GW
Samir Gupta UD
David Liu JPL
Ashique Mahmood UD

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