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BIOL 1555/PHP 2561

Methods in Informatics and Data Science for Health


The goal of this course is to develop a functional solution that uses informatics and data science approaches to address a biomedical or health challenge. Particular emphasis will be given to formalisms and algorithms used within the context of biomedical research and health care, including those used in biomolecular sequence analysis, electronic health records, clinical decision support, and public health surveillance. General programming language skills will be taught (in Julia) within these contexts. This course will provide a functional overview of methods commonly used to address challenges in biomedical and public health contexts.

Mastery of informatics and data science skills will be assessed by a final project done within a biomedical or health context. In pursuing the project, students will gain experience in the design, implementation, and evaluation of how a biomedical or health challenge can be addressed using informatics and data science. This course was developed as a Course-based Research Experience (CURE) and is designated as a Collaborative Research and Scholarly Experiences (COEX), where students will gain experience with the scientific method, its application, and presentation. For undergraduates, the final product of this course will be a poster. Graduate students will also develop a full manuscript.

Methods in Informatics and Data Science for Health
Google Classroom

Schedule - Spring 2022

Day Date Type Topic BIDSS Section
1 31-Jan Theory Introduction to Biomedical Informatics and Data Science 1.1
Practice Computing Environment Setup 2.2, 2.4
2 7-Feb Theory Electronic Health Data 1.2, 1.2.1
Practice Unix - Basics 4.1, 4.2, 4.3
3 14-Feb Theory Standards & Interoperability 1.3, 1.4,
Practice Julia - Basics (Data Types, Control Structures, File Input/Output) 6.2, 6.3, 6.4, 6.5, 6.6
- 21-Feb NO CLASS Long Weekend
4 28-Feb Theory Research Process and Software Engineering 1.5, 1.6
Practice Julia - Structures (Arrays, Sets, and Dictionaries)
5 7-Mar Theory Information Retrieval
Practice Julia - Packages, Web Services
6 14-Mar Theory Analytic Pipelines
Practice Julia - DataFrames, Statistics, Visualization
7 21-Mar Theory Machine Learning and Natural Language Processing
Practice Julia - Machine Learning, RegEx; Python - Introduction
- 28-MAR NO CLASS Spring Recess
8 4-Apr Theory/Practice Databases/SQL
Project Project Planning
10 18-Apr Project Research Topic TBD
Updates and Help
11 25-Apr Project Research Topic TBD
Updates and Help
12 2-May Project Research Topic TBD
(Reading Period) Updates and Help
13 9-May Theory Clinical Decision Support & Learning Health System
(Reading Period) Project Updates and Help
14 13-May Final FINAL PRESENTATIONS @ 2pm
(Final Exam)