This course introduces techniques for constructing mathematical and computational models of biological processes and utilizing experimental data to validate those models at many levels of organizational scale -- from genome to whole-tissue. Prerequisites: APMA 2130 or MATH 3250 or APMA 2501 - Differential Equations & Linear Algebra, and APMA 3110 or APMA 3100 or MATH 3100, and BME 2101, and BME 2104, and BME 2315 and BME major or minors

Introduces genomics and bioinformatics theory and tools to analyze large scale biological data. Specific topics covered are Introduction to Linux and R statistical programming language, computations on the high-performance computational cluster, analysis of sequencing data with applications in gene expression and protein/DNA interactions, differential expression analysis, pathway and co-expression network analysis. Prereq: (APMA 3110 or APMA 3100 or MATH 3100) and (CS 1110 or CS 1111 or CS 1112 with grade of C- or better or successfully completed CS 1110 place-out test) and BME major or minor

Intro to systems-level measurement techniques for capturing molecular information and the mathematical and computational methods for harnessing the information from these measurements to improve our understanding of cell physiology and disease. Practical implementation of the concepts in MATLAB or Python will be applied to existing, real data from published journal articles. Pre-requisites: APMA 3100 or APMA 3110, BME 2104, BME 2315, and CS 1110 or CS 1111 or CS 1112

This course will provide students with a quantitative framework for identifying and addressing important biological questions at the molecular, cell, and tissue levels. The course will focus on the interplay between methods and logic, with an emphasis on the themes that emerge repeatedly in quantitative experiments.

"We will explore engineering methods to use ""microbes as tools"" for human wellbeing, to understand and combat ""microbes as enemies"" in infectious disease, and to characterize and manipulate ""microbes as partners"" in human health and wellbeing. We will learn how facets of BME are used to test hypotheses of human/microbe relationships and to design strategies to understand and treat disease and improve human wellbeing. Prerequisites: BME 2000 AND (BME 2101 OR BME 2102) AND BME 2104 AND BME 2315"

In-depth study of a biomedical engineering area by an individual student in close collaboration with a departmental faculty member. Requires advanced analysis of a specialized topic in biomedical engineering that is not covered by current offerings. Requires faculty contact time and assignments comparable to regular course offerings. Prerequisite: instructor permission.

A year-long research project in biomedical engineering conducted in consultation with a department faculty advisor; usually related to ongoing faculty research. Includes the design, execution, and analysis of experimental laboratory work and computational or theoretical computer analysis of a problem. Requires a comprehensive report of the results. Prerequisite: third- or fourth-year standing, and instructor permission.

Students learn foundational concepts about cellular behaviors and the molecular mechanisms that drive them by communicating findings that are published in peer-reviewed scientific and engineering papers. Prereqs: coursework in Biochemistry, Cell Biology, Human Physiology/Pathology/Anatomy

This course presents organ physiology and pathology as systems that can be studied, measured, and manipulated using biomedical engineering tools and approaches by reading peer-reviewed scientific and engineering papers and discussing them in class. Prereq: knowledge of Biochem, Cell Biology, Human Physiology/Pathology/Anatomy

Students learn foundational principals of advanced research, including hypothesis formulation, experimental design, and statistical methods to assess experimental data as it relates to hypothesis testing. Prerequisites: Previous exposure to statistics and programming in a language such as Python, MATLAB, or R.