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A cloud-based learning module for biomarker discovery.

Christopher L Hemme1,2, Laura Beaudry3, Zelaikha Yosufzai4

  • 1Department of Biomedical and Pharmaceutical Sciences, College of Pharmacy, University of Rhode Island, Kingston RI, USA.

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|July 23, 2024
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Summary
This summary is machine-generated.

This study introduces a cloud-based learning module for biomarker discovery, utilizing Jupyter Notebooks with R and Bioconductor for interactive data analysis. The module offers hands-on training in omics data analysis and machine learning for identifying biomarkers.

Keywords:
biomarkerscloud computingmachine learningproteomics

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Biomarker discovery is crucial for disease diagnosis and treatment.
  • Access to interactive, cloud-based learning resources for complex data analysis is limited.
  • The NIGMS Sandbox for Cloud-based Learning aims to bridge this gap.

Purpose of the Study:

  • To develop and describe a cloud-based training module for biomarker discovery.
  • To provide interactive learning materials on analyzing omics data using R and Bioconductor.
  • To make these resources publicly available through the NIGMS Sandbox platform.

Main Methods:

  • Development of a nine-submodule training module using Jupyter Notebooks.
  • Utilization of R and Bioconductor for biomarker and omics data analysis.
  • Deployment on Google Cloud Platform for interactive cloud-based data access and analysis.

Main Results:

  • The module covers essential biomarker discovery topics, including data analysis and machine learning.
  • Interactive elements like in-line quizzes and overview videos enhance self-assessment and learning.
  • The module is publicly accessible via the NIGMS Sandbox.

Conclusions:

  • The developed module provides a valuable, interactive, and cloud-based educational resource for biomarker discovery.
  • This initiative enhances accessibility to advanced bioinformatics training.
  • The platform supports self-directed learning in omics data analysis.