Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Longitudinal Research

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...

Longitudinal Studies

Longitudinal Studies

Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...

You might also read

Related Articles

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

Sort by

Same author

Anti-LAG-3 with or without anti-PD-1 in recurrent glioblastoma: a phase 1 trial.

Nature medicine·2026

Same author

replicateFest: An R Package and Shiny App for Analysis of T Cell Receptor Repertoire Data from the Functional Expansion.

bioRxiv : the preprint server for biology·2026

Same author

Peripheral Th17 immune signature associates with excellent response to anti-PD1/anti-PD-L1 therapy across solid tumors.

Cancer immunology research·2026

Same author

Immune checkpoint inhibitor therapy after tumor-infiltrating lymphocytes in unresectable melanoma.

Journal for immunotherapy of cancer·2026

Same author

Development of the cf-MMSP assay for enhanced analytical sensitivity of methylated DNA in breast cancer liquid biopsy.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology·2026

Same author

Mutant KRAS peptide vaccine with dual checkpoint blockade in metastatic colorectal cancer: a phase I trial.

Nature communications·2026

Search research articles

Related Experiment Video

Updated: Jan 7, 2026

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

AstroID resource: a scalable, relational database structure for longitudinal biomarker discovery.

Elizabeth M Will¹, Benjamin F Green¹, Scott Carey²

¹Dermatology, Johns Hopkins University, Baltimore, Maryland, USA.

Journal for Immunotherapy of Cancer

|December 25, 2025

Summary

A new database model, AstroID, facilitates biomarker discovery by integrating longitudinal patient data with biospecimens. This flexible, scalable structure supports complex research needs in biological sciences and clinical annotation.

Keywords:

Biomarker Biopsy Melanoma Pathology Tumor microenvironment - TME

More Related Videos

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

Related Experiment Videos

Last Updated: Jan 7, 2026

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

Area of Science:

Biomedical Informatics
Genomics
Translational Research

Background:

Biological sciences generate large datasets for biomarker discovery.
Existing data models lack support for longitudinal biospecimen tracking linked to patient experiences.
A robust data model is needed for comprehensive biomarker research.

Purpose of the Study:

To develop a novel data structure for integrating clinical and biospecimen data.
To support longitudinal tracking and analysis of biospecimens for biomarker discovery.
To create a flexible, scalable, and user-friendly resource for biomedical research.

Main Methods:

A six-tier data structure was built using Research Electronic Data CAPture (REDCap).
Modules were developed for exporting data into SQL format for integration with biomarker data.
The data dictionary was aligned with existing large data models like the Human Tumor Atlas Network.

Main Results:

The AstroID resource is a searchable, flexible, and HIPAA-compliant relational database.
The structure supports thousands of patients, multimodality data, and spatial characterization of billions of cells.
Examples demonstrate its use in biomarker discovery for melanoma and other diseases.

Conclusions:

AstroID provides a valuable database model for research involving large-volume biospecimens and clinical annotation.
The structure is adaptable for characterizing longitudinal biospecimens across various disease processes.
Future integration with electronic medical records is anticipated for enhanced data synchronization.