Professional Science Master's in Natural Sciences, Biological Data Analytics Specialization

Program Overview

The Professional Science Master's in Natural Sciences with a specialization in Biological Data Analytics is a two-year graduate program designed to equip students with the skills to analyze data in the biotechnology industry. The program includes coursework in data analysis, genomics, ethics, and entrepreneurship, and prepares students for careers as data scientists, bioinformaticians, and research scientists. Students are required to take elective courses from at least two of five categories: math/computational, statistics, science, business, and communications.

Program Outline

Program Details: Professional Science Master's in Natural Sciences, Biological Data Analytics Specialization

Degree Overview:

The Professional Science Master's (PSM) program with a specialization in Biological Data Analytics is a graduate degree program designed in collaboration with leaders in the biotechnology industries. The program aims to equip students with the scientific, business, and communication skills necessary to thrive in these industries.

Objectives:

• Develop skills to analyze data from genomic, transcriptomic, proteomic, and metabolomic studies.
• Collaborate with biologists in data interpretation and experimental design.

Description:

The PSM in Natural Sciences, Biological Data Analytics Specialization is an affiliated Professional Science Master’s (PSM) degree, ensuring a strong and distinctive PSM brand. The program is designed for students seeking a graduate degree in science or mathematics who recognize the importance of developing workplace skills valued by top employers.

Outline:

The program is structured over two years and requires a minimum of 40 credits.

First Year:

• BUS 500 Foundations for Business Impact (2 credits): This course provides an introduction to business concepts and their impact on scientific research.
• DSCI 510 Linux as a Computational Platform (1 credit): This course introduces students to the Linux operating system and its applications in data analysis.
• DSCI 511 Genomics Data Analysis in Python (2 credits): This course focuses on analyzing genomic data using the Python programming language.
• NSCI 693C Graduate Seminar: Biological Data Analytics (1 credit): This seminar provides a platform for students to discuss current research and trends in biological data analytics.
• Select one course from the following (1-3 credits):
• BC 601 Responsible Conduct in Biochemistry
• BUS 505 Legal and Ethical Environment of Business
• CM 666/PHIL 666 Science and Ethics
• GRAD 544 Ethical Conduct of Research
• NSCI 575/GRAD 575 Ethical Issues in Big Data Research
• Select a minimum of 3 credits from the following (3-4 credits):
• BC 563 Molecular Genetics
• NSCI 693C Graduate Seminar: Biological Data Analytics (1 credit): This seminar continues to provide a platform for discussion and exploration of current research and trends.
• NSCI 696F Group Study: Biological Data Analytics Project Proposal (6 credits): This course involves group work on a biological data analytics project proposal.
• Select one course from the following (3-4 credits):
• ERHS 544/STAT 544 Biostatistical Methods for Quantitative Data
• STAR 512 Design and Data Analysis for Researchers II
• Electives (select from the list below with approval of advisor) (24-10 credits):
• Math/Computational Electives:
• BC 571 Quantitative Biochemistry
• CS 548/STAT 548 Topological Data Analysis
• DSCI 475 Topological Data Analysis
• MATH 532 Mathematical Modeling of Large Data Sets
• Statistics Electives:
• Science Electives:
• BC 512 Principles of Macromolecular Structure
• MIP 565/BZ 565 Next Generation Sequencing Platform/Libraries
• MIP 570 Functional Genomics
• MIP 576/BSPM 576 Bioinformatics
• Business Electives:
• MGT 430 Leadership and Social Responsibility
• MGT 450 Communications
• Communications Electives:

Careers:

The program prepares students for careers in the biotechnology industry, including:

• Data Scientist
• Bioinformatician
• Research Scientist
• Data Analyst
• Statistical Analyst

Other:

• BC 563 Molecular Genetics is generally required in either the first or second year, but may be waived if the student has sufficient prior coursework.
• Students are required to take elective courses from at least 2 of the 5 categories.
• Electives may be taken in the first or second year with the approval of an advisor.