Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Biomedical data integration: using XML to link clinical and research data sets.

Jules J Berman1, Kishor Bhatia

  • 1Pathology Informatics, Cancer Diagnosis Program, National Cancer Institute, Rockville, MD 20892, USA. bermanj@mail.nih.gov

Expert Review of Molecular Diagnostics
|June 7, 2005
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Chemotherapeutic induction of cytosolic single-stranded DNA accumulation sensitizes triple-negative breast cancer to immunotherapy.

Journal for immunotherapy of cancer·2026
Same author

A genome-wide association study identifies an African-specific locus on chromosome 21q22.12 associated with Burkitt lymphoma risk and survival.

Leukemia·2025
Same author

Clinical outcomes of DNA-damaging agents and DNA damage response inhibitors combinations in cancer: a data-driven review.

Frontiers in oncology·2025
Same author

Subtyping Burkitt Lymphoma by DNA Methylation.

Genes, chromosomes & cancer·2025
Same author

Expanding the repertoire of Antibody Drug Conjugate (ADC) targets with improved tumor selectivity and range of potent payloads through in-silico analysis.

PloS one·2024
Same author

Plasma metabolites in childhood Burkitt lymphoma cases and cancer-free controls in Uganda.

Metabolomics : Official journal of the Metabolomic Society·2024
Same journal

Bacterial respiratory infections: advances in diagnostic strategies.

Expert review of molecular diagnostics·2026
Same journal

Artificial intelligence in molecular diagnostics for pandemic preparedness.

Expert review of molecular diagnostics·2026
Same journal

Navigating PD-L1 testing in immuno-oncology: analytical robustness, clinical validation, and the role of the VENTANA SP263 assay.

Expert review of molecular diagnostics·2026
Same journal

Extracellular vesicles as diagnostic and prognostic biomarkers in non-small cell lung cancer.

Expert review of molecular diagnostics·2026
Same journal

Explainable epigenetic aging clocks: an overview of existing AI models and approaches.

Expert review of molecular diagnostics·2026
Same journal

Neuro-axonal injury biomarker serum neurofilament light chain is associated with osteoarthritis: a dual-cohort study from NHANES and UK Biobank.

Expert review of molecular diagnostics·2026
See all related articles

Extensible Markup Language (XML) facilitates biomedical data integration by linking diverse experimental and clinical data. This approach overcomes manual data correlation challenges for large-scale research, enhancing data usability.

Area of Science:

  • Biomedical Informatics
  • Data Science
  • Bioinformatics

Background:

  • Biomedical research requires integrating experimental data with clinical and pathological information for practical application.
  • Manual data correlation from patient charts and reports is inefficient for large datasets.
  • Challenges exist in the widespread availability of annotated biomedical datasets.

Purpose of the Study:

  • To review how Extensible Markup Language (XML) supports biomedical data integration.
  • To discuss obstacles hindering the availability of annotated biomedical data.

Main Methods:

  • Review of Extensible Markup Language (XML) capabilities for data integration.
  • Analysis of challenges in biomedical data annotation and accessibility.

Related Experiment Videos

Main Results:

  • Extensible Markup Language (XML) offers fundamental tools for structuring and integrating diverse biomedical data.
  • Identified challenges impede the seamless sharing and utilization of annotated research data.

Conclusions:

  • XML is a key technology for enabling robust biomedical data integration.
  • Addressing challenges in data annotation and accessibility is crucial for advancing biomedical research.