Independent Study in Biomedical Informatics (ISBDS)

This document provides ideas for research projects, and links to research plan templates, which are partially completed plans. Template files are available via the ISBDS course GitHub repository.  For ISBDS, a research plan template can vary within  biomedical science topics, but definitely includes a specific data source, overall problem statement, and methodological approach. Students will be required to complete the template to comprise a preliminary research plan for approval prior to registration. Advisors are invited to contribute research plan templates in their areas of interest and expertise, which may be based on the generic ISBDS Research Plan Template.

General Suggestions

  • Review and analysis of an important public dataset.
  • Review and analysis of an important public informatics tool.
  • Reproducing and extending a published analysis.
  • Building a database from public sources for a biomedical topic of interest. 
  • Adapt approaches, projects, and learning objectives from an existing, MOOC or other online course (e.g. Coursera, edX, Johns Hopkins, Indiana, Stanford, Hasso Plattner), with or without completing the course.
  • Respond to an online data science challenge (e.g. Kaggle).
  • Building an online app for researchers, clinicians, or patients.
  • Create or improve an open source software package.



  • PubChem analysis, descriptive or predictive
  • ChEMBL analysis, descriptive or predictive
  • DrugCentral analysis, descriptive or predictive
  • Badapple analysis, descriptive or predictive

Drug Discovery

Medical Informatics

Computational modeling

Public Health & Epidemiology

Fitness, Wellness, & Health

  • The Open Artificial Pancreas System project is an open and transparent effort to make safe and effective basic Artificial Pancreas System (APS) technology widely available to more quickly improve and save as many lives as possible and reduce the burden of Type 1 diabetes. OpenAPS means basic overnight closed loop APS technology is more widely available to anyone with compatible medical devices who is willing to build their own system.
  • ResearchKit & CareKit from Apple. CareKit allows developers to build apps that leverage a variety of customizable modules. CareKit apps will let users regularly track care plans, monitor their progress, and share their insights with care teams. CareKit is open source, developers can build upon existing modules and contribute new code to help users world wide create a bigger—and better—picture of their health.

Natural language processing (NLP) and text mining

  • PubMed named entity recognition (NER); see JensenLab Tools including Tagger.
  • Twitter sentiment analysis
  • Clustering by topic modeling
  • See code and projects from Jason Timm,

Databases and datasets