Computer Science

Computer Science: Bioinformatics

Computer Science: Bioinformatics

BS

Hours	85 Credit Hours
MAP	Major Academic Plan

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 11 courses

C S 142 - Introduction to Computer Programming 3.0

C S 224 - Introduction to Computer Systems 3.0

C S 235 - Data Structures and Algorithms 3.0

C S 236 - Discrete Structures 3.0

C S 240 - Advanced Programming Concepts 4.0

C S 252 - Introduction to Computational Theory 3.0

C S 312 - Algorithm Design and Analysis 3.0

C S 340 - Software Design and Testing 3.0

C S 360 - Internet Programming 3.0

C S 404 - Ethics and Computers in Society 2.0

C S 418 - Bioinformatics 3.0

requirement 2 Complete 2 options

Supporting courses:

option 2.1 Complete 11 courses

BIO 130 - Biology 4.0

BIO 463 - Genetics of Human Disease 3.0

BIO 465 - Bioinformatics 3.0

CHEM 105 - (Not currently offered)

ENGL 316 - Technical Communication 3.0

MATH 112 - Calculus 1 4.0

MATH 113 - Calculus 2 4.0

MATH 313 - Elementary Linear Algebra 3.0

MMBIO 240 - Molecular Biology 3.0

PHSCS 121 - Introduction to Newtonian Mechanics 3.0

PWS 340 - Genetics 3.0

option 2.2 Complete 1 course

STAT 121 - Principles of Statistics 3.0

STAT 201 - Statistics for Engineers and Scientists 3.0

requirement 3 Complete 5 courses

Note: If C S 401R or C S 498R is chosen, it must be taken for 3 hours.

C S 401R - Topics in Computer Science 3.0v

You may take this course up to 1 time.

C S 412 - Linear Programming and Convex Optimization 3.0

C S 428 - Software Engineering 3.0

C S 431 - Algorithmic Languages and Compilers 3.0

C S 450 - Introduction to Digital Signal and Image Processing 3.0

C S 452 - Database Modeling Concepts 3.0

C S 453 - Fundamentals of Information Retrieval 3.0

C S 455 - Computer Graphics 3.0

C S 456 - Introduction to User Interface Software 3.0

C S 460 - Computer Communications and Networking 3.0

C S 462 - Large-Scale Distributed System Design 3.0

C S 465 - Computer Security 3.0

C S 470 - Introduction to Artificial Intelligence 3.0

C S 478 - Tools for Machine Learning 3.0

C S 479 - Natural Language Processing 3.0

C S 484 - Parallel Processing 3.0

C S 486 - Verification and Validation 3.0

C S 498R - Undergraduate Special Projects 3.0v

Program Outcomes

Biological Background

Students understand the biological concepts that will allow them to write impactful bioinformatics algorithms.

Computational Practice

Students can implement significant programming projects. Students will perform analysis, specification, design, implementation, and testing resulting in quality computer software solutions. Students will use data structures, algorithms, programming languages, and software engineering techniques in their programming.

Computational Theory

Students will use theoretical concepts in their programming. Students will have the theoretical computer science background and the mathematical and analytical maturity necessary to allow them to follow and adapt to technological changes in their discipline or to enter graduate programs in Computer Science. Students will use automata theory, mathematics, and abstraction to analyze problems and their algorithmic solutions.