The Professional Science Master's (PSM) program with a specialization in Biological Data Analytics is a graduate degree program that was designed in coordination with leaders in the biotechnology industries in order to ensure that students will have the scientific, business, and communication skills required to be competitive for jobs in these industries. Students will develop skills that will allow them to analyze data from genomic, transcriptomic, proteomic, and metabolomic studies to find statistically relevant information, while interfacing with biologists in data interpretation and experimental design.

Effective Fall 2019

Because this program is intended to serve students with a wide range of backgrounds, each student must work with an advisor to determine an appropriate selection of courses. 

Plan of Study Grid
First YearCredits
BUS 500Business Systems and Processes2
DSCI 510Linux as a Computational Platform1
DSCI 511Genomics Data Analysis in Python2
NSCI 693CGraduate Seminar: Biological Data Analytics1
Select one course from the following:1-3
Responsible Conduct in Biochemistry 
Legal and Ethical Environment of Business 
Science and Ethics 
Ethical Conduct of Research 
Ethical Issues in Big Data Research 
Select one course from the following:3-4
R Programming for Research 
Design and Data Analysis for Researchers I: R Software 
Select a minimum of 3 credits from the following:3-4
Molecular Genetics 
Nucleic Acids for Non-Life Scientists 
Protein Basics for NonBiologists 
RNA Biology 
 Total Credits13-17
Second Year
DSCI 512RNA-Sequencing Data Analysis1
MGT 340Fundamentals of Entrepreneurship3
NSCI 693CGraduate Seminar: Biological Data Analytics1
NSCI 696FGroup Study: Biological Data Analytics Project Proposal6
Select one course from the following:3-4
Molecular Genetics 
RNA Biology 
Select one course from the following:3-4
Biostatistical Methods for Quantitative Data 
Design and Data Analysis for Researchers II 
Electives (select from the list below with approval of advisor)24-10
 Total Credits21-29
 Program Total Credits:40

A minimum of 40 credits are required to complete this program. 

Electives

Math/Computational Electives:
Quantitative Biochemistry
Bioinformatics Algorithms
Topological Data Analysis
Mathematical Modeling of Large Data Sets
Statistics Electives:
SAS and Epidemiologic Data Management
Mass Spectrometry Omics-Methods and Analysis
Design and Data Analysis for Researchers I: SAS Software
Science Electives:
Principles of Macromolecular Structure
Molecular Regulation of Cell Function
Gene Expression
RNA Biology
Next Generation Sequencing Platform/Libraries
Functional Genomics
Bioinformatics
Business Electives:
Leadership and Social Responsibility
Biomedical Entrepreneurship I
Communications Electives:
STEM Communication