OncoMX

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

Statistics at a Glance

Cancer Terms Biomarker Stats Bgee Stats BioMuta Stats BioXpress Stats Proteins Reactome Stats

Summary Statistics

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

Normal Expression Filters

Gene Symbol

Expression Call

Call Quality

Uberon anatomical entity name

Uberon developmental stage name

Literature Mining Filters

Gene Symbol

Gene Mention

Disease Ontology

Disease Mention

Mutation Mention

Expression change

Mutation Type

Differential Expression Filters

Gene Symbol

TCGA cancers

DO cancer type

Log2 F.C.

P value

Gene Symbol	UniProtKB/SwissProt AC	EDRN Biomarker	# BioMuta Mutations	# BioXpress Cancers	# Reactome Pathways	# Bgee Datasets

About

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.