Bioinformatics (BS)
Download as PDF
Variable Credit Min
Variable Credit Max
Major Academic Plan
Title
Learning Outcome
Title
Learning Outcome
Title
Learning Outcome
Program Requirements
Requirement 1 — Complete 7 Courses
course - Biology 4.0
course - Introduction to Bioinformatics 3.0
course - Stat Analysis for Biologists 4.0
course - Bioinformatics Algorithms 3.0
course - Capstone in Bioinformatics 3.0
course - Molecular Biology 3.0
course - Genetics 3.0
Requirement 2 — Complete 1 of 2 Courses
course - Evolutionary Medicine 2.0
course - Evolutionary Biology 4.0
Requirement 3 — Complete 8 Courses
course - Gen College Chem 1+Lab Integr 4.0
course - General College Chemistry 2 3.0
course - Intro to Computer Science 3.0
course - Data Structures 3.0
course - Discrete Structure 3.0
course -Adv Software Construction 4.0
course - Algorithm Design & Analysis 3.0
course - Calculus 1 4.0
Requirement 4 — Complete 8 Hours
Note: Up to 2 total credit hours of BIO 194, BIO 399R, and/or BIO 494R are allowed. Note: Either BIO 370 or PHIL 212R can be used to partially fulfill this requirement, but not both.
course - Intro to Mentored Research 0.5
course - Ecology 3.0
course - Computational Cancer Biology 3.0
course - Bioethics 2.0
course - Capstone in Biodiversity & Con 3.0
course - Genetics of Human Disease 3.0
course - Genomics 3.0
course- Mentored Research - You may take up to 2.0 credit hours 0.5v
course - Advanced Genetic Analysis 3.0
course - Evolutionary & Ecol Modeling 2.0
course - Population Genetics 4.0
course - Machine Learning for Bio 3.0
course - Cell Biology 3.0
course - Advanced Physiology 3.0
course - Developmental Biology 3.0
course - Organic Chemistry 1 3.0
course - Organic Chemistry 2 3.0
course - Organic Chem Lab-Nonmajors 1.0v
course - Biochemistry 3.0
course - Mechanisms of Molecular Biol 3.0
course- Structural Biochemistry 3.0
course - Web Programming 3.0
course- Intro to Machine Learning 3.0
course - Software Design 3.0
course - Graphics and Image Processing 3.0
course - Computer Vision 3.0
course - Database Modeling Concepts 3.0
course - Intro Artificial Intelligence 3.0
course - Deep Learning 3.0
course - Calculus 2 4.0
course - Elementary Linear Algebra 2.0
course - Computational Linear Algebra 1.0
course - Calculus of Several Variables 3.0
course- Ordinary Differential Equation 3.0
course - Genetic Counseling 3.0
course - Microbial Genetics 4.0
course - Intro to Medical Ethics - You may take once 3.0
course - Statistical Computing 3.0
course- Nonparametric Stat Methods 3.0
course - Experimental Design 3.0
Requirement 5 — Complete 1 Course
course - Field Exam and Exit Survey 0.0