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Computer Science: Bioinformatics (BS)

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Computer Science Bachelors BS

Variable Credit Min

79

Variable Credit Max

81

Major Academic Plan

Title

Computational Practice

Learning Outcome

Students will design and implement significant computer programs that meet a human need and will develop expertise in bioinformatics. See the Computer Science BS program for general assessments shared across all emphases.

Title

Computational and Biological Theory

Learning Outcome

Students will analyze problems and their algorithmic solutions using theoretical concepts from computer science and biology.See the Computer Science BS program for general assessments shared across all emphases.

Title

Career Preparation

Learning Outcome

Students will have sufficient maturity in computer science to work in a professional setting in computer science or bioinformatics or to enter a graduate program.See the Computer Science BS program for general assessments shared across all emphases.

Title

Diversity, Equity and Inclusion

Learning Outcome

Our program is accessible to everyone including women minorities and those new to programming and provides an equal opportunity for every student to succeed.See the Computer Science BS program for general assessments shared across all emphases.

Program Requirements

Personnel in the College of Physical and Mathematical Sciences Advisement Center will advise regarding core courses and suggested general education. Questions regarding curriculum and career decisions should be directed to the undergraduate advisor in the Computer Science Department.

Note: All hours of credit applied toward a major in computer science must be of C- or better and must be taken within eight years of declaring the computer science major. Any exceptions must be approved by the department. Students may choose to graduate under later requirements by updating their date of entry into the major at the college advisement center.

Requirement 1 — Complete 8 Courses 

Computer Science core:

course - Intro to Computer Science 3.0

course - Computer Systems 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 - Systems Programming 3.0

course - Ethics & Computers in Society 2.0

Requirement 2 — Complete 7 Courses 

Biology core:

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 3 — Complete 5 Courses 

Supporting courses:

course - Gen College Chem 1+Lab Integr 4.0

course - Calculus 1 4.0

course - Elementary Linear Algebra 2.0

course - Computational Linear Algebra 1.0

course - Technical Communication 3.0

Requirement 4 — Complete 1 of 2 Courses 

course - Evolutionary Medicine 2.0

course - Evolutionary Biology 4.0

Requirement 5 — Complete 1 of 2 Courses 

course - Intro to Machine Learning 3.0

course - Deep Learning 3.0

Requirement 6 — Complete 12 hours

Courses will not double count between Requirement 5 and Requirement 6.

Option 6.1 — Complete at least 6 hours up to 12 hours

Complete up to 12 hours from the following courses

course - Genetics of Human Disease 3.0

course - Introduction to HCI 3.0

course - Web Programming 3.0

course - Test, Analysis, & Verification 3.0

course - Concepts of Programng Lang 3.0

course - Operating Systems Design 3.0

course - Graphics and Image Processing 3.0

course - Advanced Techniques in HCI 3.0

course - Adv Algorithms & Probl Solving 3.0

course - Topics in Computer Science - You may take up to 3.0 credit hours 1.0v

course - Software Business 3.0

course - Linear Prog/Convx Optimization 3.0

course - Software Engineering 3.0

course - Algorithmic Lang & Compilers 3.0

course - Computer Vision 3.0

course - Database Modeling Concepts 3.0

course - Fund of Information Retrieval 3.0

course - Computer Graphics 3.0

course - Mobile and Ubiquitous HCI 3.0

course - Comp Comms & Networking 3.0

course - Distributed System Design 3.0

course - Computer Security 3.0

course - Blockchain Technologies 3.0

course - Intro Artificial Intelligence 3.0

course - Voice Interfaces 3.0

course - Intro to Machine Learning 3.0

course - Deep Learning 3.0

C S 478 - Tools for Machine Learning - This course is no longer available for registration and will count only if you completed it while it was offered. Please see your college advisement center for possible substitutions. 3.0

course - Intro to Machine Translation 3.0

course - Soft Eng Capstone 1 3.0

course - Soft Eng Capstone 2 3.0

course - Data Science Capstone 1 3.0

course - Data Science Capstone 2 3.0

course - Verification and Validation 3.0

course - Computing Competitions - You may take up to 3.0 credit hours 3.0

course - Robust Control 3.0

C S 575 - Intro to Network Science - This course is no longer available for registration and will count only if you completed it while it was offered. Please see your college advisement center for possible substitutions. 3.0

course - Theory of Predictive Modeling 3.0

Option 6.2 — Complete up to 6 hours

course - Undergraduate Research - You may take up to 6.0 credit hours 3.0

course - Undergraduate Special Projects - You may take up to 3.0 credit hours 1.0v

Requirement 7 — Obtain confirmation from your advisement center that you have completed the following: 

Complete Senior Exit Interview with the CS department during your last semester or term.