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'''1. Where can I find more information on the project?''' The project webpage can be found [https://biomarkerkb.org/about/ here].
The frequently asked questions are a collection of user questions related to the BiomarkerKB frontend, backend, and data. The answers to these questions contain definition and explanations of terms, such as Single Biomarker or Multicomponent Biomarker. The list of questions is subdivided into questions related to [[#Biomarker FAQs|biomarker]] and [[#General FAQs|general questions]]. You can also use the BiomarkerKB [https://biomarkerkb.org/contact-us/ contact] page to reach out to us with any additional questions or queries.


'''2. Is the project repository publicly available?''' You can view all the project repositories [https://github.com/clinical-biomarkers here].
== General FAQs ==
=== Where can I find more information on the project? ===
* The project webpage can be found [https://biomarkerkb.org/about/ here].


'''3. What are the biomarker scores and how are scores assigned for the biomarkers?''' The biomarker-score-calculator and default scoring algorithm can be found [https://github.com/clinical-biomarkers/biomarker-score-calculator here]. The biomarker scores can be seen on the full JSON data model responses from the API.
=== Is the project repository publicly available? ===
* You can view all the project repositories [https://github.com/clinical-biomarkers here].


'''4. Why are some biomarkers assigned a score of 0?''' Biomarkers with a default score of 0 are manually assigned a 0 score and are pending a manual review. The review of the biomarker can include a spot check, full manual quality checking, NLP based methods, and discussions with the submitter/resource. Until the review is complete the biomarker will keep a score of 0 and after the review is complete the biomarker will be scored using the biomarker score calculator tool.
=== What are the biomarker scores and how are scores assigned for the biomarkers? ===
* The biomarker-score-calculator and default scoring algorithm can be found [https://github.com/clinical-biomarkers/biomarker-score-calculator here]. The biomarker scores can be seen on the full JSON data model responses from the API.


'''5. How to download all the 'current' dataset files using CLI?''' The BiomarkerKB dataset can be downloaded using command - <code>wget -r -l1 -np -nd -R "index.html*" <nowiki>https://data.biomarkerkb.org/ln2data/releases/data/current/reviewed/</nowiki></code>
=== Why are some biomarkers assigned a score of 0? ===
* Biomarkers with a default score of 0 are manually assigned a 0 score and are pending a manual review. The review of the biomarker can include a spot check, full manual quality checking, NLP based methods, and discussions with the submitter/resource. Until the review is complete the biomarker will keep a score of 0 and after the review is complete the biomarker will be scored using the biomarker score calculator tool.
 
=== How to download all the current dataset files using CLI? ===
* The BiomarkerKB dataset can be downloaded using the command <code>wget -r -l1 -np -nd -R "index.html*" <nowiki>https://data.biomarkerkb.org/ln2data/releases/data/current/reviewed/</nowiki></code>
 
== Biomarker FAQs ==
 
=== What is the difference biomarker types and biomarker roles? ===
'''Biomarker type''' refers to the methodology or modality used to measure a biomarker. According to the FDA-NIH BEST glossary, biomarker types include molecular, histologic, radiographic, and physiologic characteristics.<ref>[https://www.fda.gov/drugs/biomarker-qualification-program/about-biomarkers-and-qualification#BEST_Glossary About Biomarkers and Qualification – FDA BEST Glossary]</ref>
 
'''Biomarker role''' describes the clinical or scientific purpose a biomarker serves. Recognized biomarker roles are:
 
* Susceptibility/risk
* Diagnostic
* Monitoring
* Prognostic
* Predictive
* Pharmacodynamic/response
* Safety
 
For further detail on biomarker roles, see the BEST Resource.<ref>[https://www.ncbi.nlm.nih.gov/books/NBK338448/ BEST (Biomarkers, EndpointS, and other Tools) Resource – NCBI Bookshelf]</ref>
 
=== What is the difference between single-component, multi-component, and composite biomarkers? ===
Biomarkers are classified into three categories based on how many components they comprise and how those components relate to one another.
==== Key definitions ====
; Entity
: The biological object or concept being assessed. See [https://github.com/clinical-biomarkers/biomarker-controlled-vocabulary entity examples in the Biomarker Controlled Vocabulary].
; Component
: A single instance of an assessed entity — that is, a single measured analyte.
==== Single-component biomarker ====
A single-component biomarker consists of exactly one component (a single measured analyte).
 
For further detail, see [[Single biomarker]].
==== Multi-component biomarker ====
A multi-component biomarker (MCB) is a defined combination or defined set of two or more individual biomarkers whose values, when considered together in a specified way, yield a meaningful result (e.g., a lipid panel of total cholesterol, LDL, HDL, and triglycerides). MCBs have two subtypes:
* Integrative biomarker
: An integrative biomarker entity is composed of multiple component measurements that are generated separately, often using different measurement methods or data sources (e.g., imaging measurements, EEG features, or laboratory values) rather than as part of a single omics experiment. All components are known. A defined mathematical or computational algorithm combines these separate measurements into a single quantitative value, score, or index that is interpreted to have a specific biological, clinical, or diagnostic meaning.
* Pattern biomarker
: A pattern biomarker entity is composed of a defined set of component measurements that are generated or analyzed together to identify a pattern or signature result. All components may not be known. This may include omics-derived patterns — such as proteomic, metabolomic, glycomic, transcriptomic, or multi-analyte signatures — as well as other multiplex measurement panels. The key feature is that component measurements are interpreted collectively, rather than individually, to produce a biomarker result with a specific meaning.
 
For further detail, see [[Multi-component biomarker]].
==== Composite biomarker ====
A composite biomarker entity is one in which the entity being measured is itself composed of multiple molecular components that together form a single structural or functional unit. Components may be covalently linked (e.g., a glycan attached to a protein) or associated through non-covalent interactions (e.g., protein complexes or RNA–protein complexes). In some cases, the measurement may reflect the composite entity as a whole without establishing which individual component is responsible for the measured signal. The defining feature is that the molecular components are physically associated and are being considered together as one biomarker entity.
 
For further detail, see [[Multi-entity biomarker]].
 
==== Notes on Terminology ====
These definitions are informed by the FDA-NIH Biomarker Working Group terminology<ref>[https://www.ncbi.nlm.nih.gov/books/NBK326791/ BEST Resource: Biomarker Terminology – NCBI Bookshelf]</ref><ref>[https://www.ncbi.nlm.nih.gov/books/NBK610679/ BEST Resource: Additional Terminology – NCBI Bookshelf]</ref> but have been adapted in places to better describe the specific biomarker concepts represented in BiomarkerKB.
 
== References ==
Daniall Masood, Mariia Kim, Jeet Vora, Robel Kahsay, Patrick McNeely, Sean Kim, Cyrus Chun Hong Au Yeung, Sujeet Kulkarni, Darren A. Natale, Srinivasan Ramachandran, Shakti Gupta, Mano Maurya, Cristian G. Bologa, Thomas S. DeNapoli, Vincent T. Metzger, Praveen Kumar, Nasheath Ahmed, John Erol Evangelista, Nia Lingam, Sean C. Kelly, Jorge L. Sepulveda, Avi Ma’ayan, Jonathan Silverstein, Deanne M. Taylor, Daniel J. Crichton, Ashish Mahabal, Jeremy J. Yang, Christophe G. Lambert, Shankar Subramaniam, Michael Tiemeyer, Rene Ranzinger, Raja Mazumder (2026). '''"BiomarkerKB: An Integrated Knowledgebase Supporting Biomarker-Centric Exploration of Biomedical Data"'''. ''Patterns'', DOI 10.1016/j.patter.2026.101636.
 
<references />
== External links ==
 
*'''BiomarkerKB''': https://biomarkerkb.org/
<div style="float: right;">  [[#top|[top]]]</div>

Latest revision as of 17:18, 19 September 2026

The frequently asked questions are a collection of user questions related to the BiomarkerKB frontend, backend, and data. The answers to these questions contain definition and explanations of terms, such as Single Biomarker or Multicomponent Biomarker. The list of questions is subdivided into questions related to biomarker and general questions. You can also use the BiomarkerKB contact page to reach out to us with any additional questions or queries.

General FAQs

Where can I find more information on the project?

  • The project webpage can be found here.

Is the project repository publicly available?

  • You can view all the project repositories here.

What are the biomarker scores and how are scores assigned for the biomarkers?

  • The biomarker-score-calculator and default scoring algorithm can be found here. The biomarker scores can be seen on the full JSON data model responses from the API.

Why are some biomarkers assigned a score of 0?

  • Biomarkers with a default score of 0 are manually assigned a 0 score and are pending a manual review. The review of the biomarker can include a spot check, full manual quality checking, NLP based methods, and discussions with the submitter/resource. Until the review is complete the biomarker will keep a score of 0 and after the review is complete the biomarker will be scored using the biomarker score calculator tool.

How to download all the current dataset files using CLI?

  • The BiomarkerKB dataset can be downloaded using the command wget -r -l1 -np -nd -R "index.html*" https://data.biomarkerkb.org/ln2data/releases/data/current/reviewed/

Biomarker FAQs

What is the difference biomarker types and biomarker roles?

Biomarker type refers to the methodology or modality used to measure a biomarker. According to the FDA-NIH BEST glossary, biomarker types include molecular, histologic, radiographic, and physiologic characteristics.[1]

Biomarker role describes the clinical or scientific purpose a biomarker serves. Recognized biomarker roles are:

  • Susceptibility/risk
  • Diagnostic
  • Monitoring
  • Prognostic
  • Predictive
  • Pharmacodynamic/response
  • Safety

For further detail on biomarker roles, see the BEST Resource.[2]

What is the difference between single-component, multi-component, and composite biomarkers?

Biomarkers are classified into three categories based on how many components they comprise and how those components relate to one another.

Key definitions

Entity
The biological object or concept being assessed. See entity examples in the Biomarker Controlled Vocabulary.
Component
A single instance of an assessed entity — that is, a single measured analyte.

Single-component biomarker

A single-component biomarker consists of exactly one component (a single measured analyte).

For further detail, see Single biomarker.

Multi-component biomarker

A multi-component biomarker (MCB) is a defined combination or defined set of two or more individual biomarkers whose values, when considered together in a specified way, yield a meaningful result (e.g., a lipid panel of total cholesterol, LDL, HDL, and triglycerides). MCBs have two subtypes:

  • Integrative biomarker
An integrative biomarker entity is composed of multiple component measurements that are generated separately, often using different measurement methods or data sources (e.g., imaging measurements, EEG features, or laboratory values) rather than as part of a single omics experiment. All components are known. A defined mathematical or computational algorithm combines these separate measurements into a single quantitative value, score, or index that is interpreted to have a specific biological, clinical, or diagnostic meaning.
  • Pattern biomarker
A pattern biomarker entity is composed of a defined set of component measurements that are generated or analyzed together to identify a pattern or signature result. All components may not be known. This may include omics-derived patterns — such as proteomic, metabolomic, glycomic, transcriptomic, or multi-analyte signatures — as well as other multiplex measurement panels. The key feature is that component measurements are interpreted collectively, rather than individually, to produce a biomarker result with a specific meaning.

For further detail, see Multi-component biomarker.

Composite biomarker

A composite biomarker entity is one in which the entity being measured is itself composed of multiple molecular components that together form a single structural or functional unit. Components may be covalently linked (e.g., a glycan attached to a protein) or associated through non-covalent interactions (e.g., protein complexes or RNA–protein complexes). In some cases, the measurement may reflect the composite entity as a whole without establishing which individual component is responsible for the measured signal. The defining feature is that the molecular components are physically associated and are being considered together as one biomarker entity.

For further detail, see Multi-entity biomarker.

Notes on Terminology

These definitions are informed by the FDA-NIH Biomarker Working Group terminology[3][4] but have been adapted in places to better describe the specific biomarker concepts represented in BiomarkerKB.

References

Daniall Masood, Mariia Kim, Jeet Vora, Robel Kahsay, Patrick McNeely, Sean Kim, Cyrus Chun Hong Au Yeung, Sujeet Kulkarni, Darren A. Natale, Srinivasan Ramachandran, Shakti Gupta, Mano Maurya, Cristian G. Bologa, Thomas S. DeNapoli, Vincent T. Metzger, Praveen Kumar, Nasheath Ahmed, John Erol Evangelista, Nia Lingam, Sean C. Kelly, Jorge L. Sepulveda, Avi Ma’ayan, Jonathan Silverstein, Deanne M. Taylor, Daniel J. Crichton, Ashish Mahabal, Jeremy J. Yang, Christophe G. Lambert, Shankar Subramaniam, Michael Tiemeyer, Rene Ranzinger, Raja Mazumder (2026). "BiomarkerKB: An Integrated Knowledgebase Supporting Biomarker-Centric Exploration of Biomedical Data". Patterns, DOI 10.1016/j.patter.2026.101636.

  1. ↑ About Biomarkers and Qualification – FDA BEST Glossary
  2. ↑ BEST (Biomarkers, EndpointS, and other Tools) Resource – NCBI Bookshelf
  3. ↑ BEST Resource: Biomarker Terminology – NCBI Bookshelf
  4. ↑ BEST Resource: Additional Terminology – NCBI Bookshelf

External links

  [top]
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