BiomarkerKB Resource Integration

BiomarkerKB collects data from a wide range of resources. Not all collected data are directly integrated into the core data model; some are included as contextual annotations or cross-references to enrich existing entries.

Resources for Exploration

• Marker Database
• ResMarkerDB
• SalivaDB
• GlycanAge Publications
• Cancer Genome Interpreter (Biomarkers)
• Glycan Biomarkers (code)
• Alliance Genome

For suggestions of additional biomarker data resources, please contact: mazumder_lab@gwu.edu

Data Sources

GWAS

Status: Direct integration into data model

• Genome-wide association studies (GWAS) provide biomarkers in the form of SNPs.
• The GWAS Catalog includes SNPs associated with a wide range of diseases.
  • Preliminary curation has only focused on cancer.
  • As of 12/11/2026, biomarkers for all available conditions in the GWAS Catalog have been integrated.
• License: CC BY-NC 4.0

MetaKB

Status: Direct integration into data model

• Provides harmonized associations between cancer genomic variants, diseases, and therapeutic evidence.
• Aggregates and standardizes variant interpretation data from six major knowledgebases:
  • Clinical Interpretation of Variants in Cancer (CIViC) (integrated)
  • OncoKB (restricted from commercial use)
  • The Jackson Laboratory Clinical Knowledgebase (JAX-CKB) (restricted from commercial use and has share-alike requirements for non-commercial use)
  • MolecularMatch (restricted from commercial use)
  • Precision Medicine Knowledgebase) (pending integration)
  • Cancer Genome Interpreter (CGI) – through its Cancer Biomarkers Database component (integrated)
• Enables mapping of:
  • Variant → Disease → Drug relationships
  • Evidence levels and citations
  • Ontology-aligned entities (genes, variants, diseases, drugs)
• Notes:
  • Requires validation of entity mappings against BiomarkerKB schema
• Focused on somatic variant–based biomarkers; contextual attributes such as tissue type, therapy response, or evidence type can be inferred or imputed where not directly specified.
• Manual curation may be required for entries with incomplete evidence annotation or lacking standard ontology references.
• Integration approach: direct mapping of variant, condition, and evidence entities; cross-references retained to original data sources.
• License: Aggregated data are available for non-commercial, research use only, respecting constituent licenses:
  • CIViC – CC0 (Public Domain)
  • PMKB – CC-BY 4.0
  • CGI – CC0 for biomarkers database, CC-BY-NC 4.0 for tool
  • JAX-CKB – CC-BY-NC-SA 4.0
  • OncoKB – custom non-commercial license
  • MolecularMatch – restricted commercial use
  • MetaKB codebase – MIT license
• Overall usage requires adherence to non-commercial research terms; commercial use needs separate permissions from individual data providers.

Glycan LLM Biomarkers

Status: Direct integration into data model

• LangChain LLM method used to collect biomarkers from PubMed Central abstracts
• Method identifies glycan entities and changes mentioned in them associated to disease

Note: only biomarkers with assessed_entity_type: protein were integrated, with the goal of expanding to glycan entity types once the Glycan Structure Dictionary is finalized.

Top 50 Biomarkers

Status: Direct integration into data model

• Biomarkers collected during Summer Volunteership
• Volunteers identified top 50 biomarker entities from BiomarkerKB
• Using this information the top 50 biomarker entities were searched in PubMed
• 100 biomarkers were manually curated

EDRN

Status: Sample integration into data model

• Cancer biomarkers.
• Sample of EDRN Biomarkers provided from EDRN LLM method
• Biomarkers are extracted from free text in EDRN publicly available biomarkers

LOINC

Status: Direct integration into data model

• Metabolite data only
• We are currently working with the Metabolomics Workbench group to get the complete data

OncoKB

Status: Cross-Reference

• Provides useful information on drugs and therapy options for different biomarker entities.
• Also provides information based on what condition the entity is related to.
• License: A license is required to use OncoKB for commercial and/or clinical purposes, and to access OncoKB data programmatically for academic purposes.
• Paid license is required
• Cross-reference from biomarkers in BiomarkerKB to the appropriate drug information and therapy information is the best solution.

HPO

Status: Cross-Reference

• HPO provides disease and entity associations.
• Does not provide a change within the entity so we cannot collect biomarker data from here.
• However we can use it as a cross-reference within our cross-referencing section.
• Provides cross-reference to OMIM, SNOMED, and MONDO.

UniProtKB

Status: Direct integration into data model

• Can provide biomarker (change in entity), entity, condition, and sampling data.
• This data is in a text file that has to be reviewed fully and to make sure it will be able to be automatically extracted.
• Contextual information can be imputed if necessary.
• In UniProt there are found_in and entries that are actual biomarkers:
  • found_in will get a cross-reference;
  • actual biomarkers will be directly integrated.
• Manual curation of 56 reviewed entries with mention of "biomarker" in flat text file.
• License: Creative Commons Attribution 4.0 International (CC BY 4.0).

CIViC

Status: Direct integration into data model

• Clinical Interpretation of Variants in Cancer (CIViC).
• Provides cancer biomarkers in form of DNA mutations (dbSNPs).
• Platform provides clinicians treatment options for patients based on unique tumor profile.
• License: Creative Commons Attribution-NonCommercial 4.0 International License.

ClinVar

Status: Direct integration into data model

• Public archive of reports of human variations classified for diseases and drug responses.
• Provides biomarkers for all disease, but we have only curated cancer biomarkers for now.
  • dbSNPs
  • File is really big but will go back and use existing script to map all biomarkers from here into the data model.
• License: Creative Commons Attribution-NonCommercial 4.0 International License.

Note: Only biomarkers from "cancer" and "carcinoma" tags were pulled. Pending integration of biomarkers for all diseases.

MarkerDB

Status: Cross-Reference

• Provides a lot of useful biomarker data and cross-references other resources as well.
• Information includes: panel information, abnormal levels of biomarkers by disease, structural information, etc.
• Annotations that can be cross-referenced include the above.
• By cross-referencing, BiomarkerKB will allow users to find more information for specific biomarkers and move towards the goal of being a comprehensive resource for biomarkers.
• License: Creative Commons Attribution-NonCommercial 4.0 International License.

Metabolomics Workbench

Status: Direct integration into data model

Data provided by Metabolomics Workbench

• Metabolite biomarkers utilized in the uniform newborn screening program.
• Detect treatable disorders that are life threatening or having long-term morbidity, before they become symptomatic.

OncoMX

Status: Direct integration into data model

• Integrated cancer mutation and expression resource for exploring cancer biomarkers
• Manual curation effort by GWU and JPL
• Over 600 single and panel biomarkers
• License: Creative Commons Attribution-NonCommercial 4.0 International License.

OpenTargets

Status: Direct integration into data model

• Collects potential drug targets and therapeutic targets.
• Some effort was required to find the correct biomarker data.
• 1200 biomarkers collected.
  • dbSNPs related to cancer and other disease
• License: Creative Commons Attribution-NonCommercial 4.0 International License.

Note: Only cancer data was integrated.

PubMed Central Biomarker Gene Set

Status: Direct integration into data model

Data provided by Avi Ma'ayan's LINCS group

• This data set was created through manual curation of biomarker gene sets on Pubmed Central using the results of gene sets returned from Rummagene.
• Using the outputted search results within the Rummagene web server, we manually identified publications that associated different conditions and environmental exposures to biomarker gene sets.
• The biomarker gene sets were retrieved through the validation of the gene mentioned within each of the publications.
• The primary use case for this data is to identify biomarker panels/ gene sets associated with conditions.

SenNet

Status: Direction integration into data model

• Cell senescence biomarkers from SenNet group
• Biomarker data was collected and incorporated however biomarker field was incomplete and data integrated was given a score of -2
• Data is still valuable as contextual data and can be revisited to complete biomarker field in future

For infomation about Cross-references and Annotations in BiomarkerKB please visit - Xrefs and annotations

Pending Resources

biomarker.org

Reached out on March 17th, 2026 regarding data access and sent follow-up communications; however, no response was received.

caDSR

The Cancer Data Standards Registry and Repository (caDSR) is a metadata registry, not a biomarker knowledge source. It defines Common Data Elements (CDEs), including field names, definitions, and controlled value sets, but does not contain biomarker-condition relationships or evidence.

For BiomarkerKB, it could potentially be valuable for schema standardization rather than data ingestion. For example, align fields like condition, specimen, and entity type to controlled vocabularies (via NCI Thesaurus).

Recommendation: not ingestible as a data source.