Figure 1: Overview of an integrated biomedical data, information, and knowledge lifecycle, showing the contributions of theories and methods associated with Big Data, Biomedical Data Science, and Biomedical Informatics (BMI). For each phase of the model, exemplary contributions to such theory and practice that have been generated by the BMI community over the last several decades are shown.

Throughout their training, learners will interact with patients, providers, and the healthcare data ecosystem in addition to working at the bench. The BIDS program promotes collaboration and partnerships in solving problems in clinical practice, individual and population health, and biomedical research, through the optimal use of information. Due to its interdisciplinary nature, the BIDS program offers learners great flexibility when creating individual education plans based on interests, experience, and future goals. 

Examples of our core research tracks and subfields are listed below: 

Biostatistics and Data Science Research Track: The goal of the Biostatistics and Data Science track is to train independent and innovative researchers who will contribute to the development and application of cutting-edge statistical and data science methodologies in health science disciplines. The track provides a balance of theory, methods, and applications of biostatistics and data science that are central to modern interdisciplinary research. Under the supervision of advisors, PhD students participate in the design of clinical studies and are involved in the analysis, inference, and interpretation of these studies. 

Biomedical Informatics Research Track: Through the Biomedical Informatics track, students will have training and research opportunities in the five subdisciplines of biomedical informatics. The five areas as defined by the American Medical Informatics Association (AMIA), the largest professional scientific community in the field of biomedical informatics:

1. Applied Clinical Informatics (ACI) focuses on supporting and elevating clinical informatics practice through research translation, which is essential to fill the gaps between practice and research. ACI involves the application of innovative measurement and informatics approaches to inform and improve clinical practice.
2. Consumer Health Informatics (CHI) involves views from consumers or patients and focuses on information structures and processes to empower individual’s management of their own health. CHI investigates consumers' needs and integrates consumers' preferences into health information systems.
3. Clinical Research Informatics (CRI) involves the use of informatics in the discovery and management of new knowledge relating to health and disease. Specifically, CRI manages information related to clinical trials as well as secondary use of clinical data.
4. Translational Bioinformatics (TBI) is the development of storage, analytic, and interpretive methods to optimize the transformation of increasingly voluminous biomedical data into proactive, predictive, preventative, and participatory health.
5. Population Health Informatics (PopHI) integrates aspects of public health, clinical informatics, and health care delivery with the target of improving health care system effectiveness and the well-being of communities and populations.

There is a wide range of research interests between faculty affiliated with the BIDS program, some of which include:

Human genetic analysis
Telemedicine & mobile health
Cognitive computing & machine learning
Systems biology
Epidemiology & public health
Neuroimaging
Computational mass spectrometry & proteomics
Survival Analysis
Clinical decision support & workflow