The Computational Emphasis specializes inthe development and use of the next generation of bioinformatics tools and software.

Program Objectives

Graduates will be effective members of multi-disciplinary teams in industry or academia.

Some of the graduates will engage in advanced studies in informatics.

Learning Outcomes:

Graduates of the Computational  Emphasis will have the skills to use and develop bioinformatic tools and resources.

All students must take four core courses:

• Biostatistics 1 (MEDB 5501)
• Biostatistics 2 (MEDB 5102)
• Clinical Research Methods (MEDB 5110)
• Responsible Conduct of Research (SGS 5550)

 

Students in the Computational Emphasis Area must also take these four courses:

• Database Design/Management (CS 470 or 471)
• Introduction to Bioinformatics (CS 5566)
• Medical Informatics (MEDB 5120), and
• Machine Learning in Bioinformatics (CS 5567).

Students can elect to do a 6 credit hour thesis or a 3 credit hour capstone plus one additional elective

All students should take two electives if they are selecting the thesis option and three if they are selecting the practicum option. Students should work with their advisor to determine the most appropriate electives. A list of suggested electives is below:

• Advanced Software Engineering (CS5551)
• Knowledge Discovery & Management (CS5560)
• Foundations of Computational Intelligence (CS5590CI)
• Neural and Adaptive Systems (ECE5590NN)
• Advanced Biomedical Signal Processing (ECE5590BP)
• Biomedical Image Processing (ECE5590B)
• Pattern Recognition (ECE5590PR)
• Design and Analysis of Algorithms (CS5592)
• Architecture of Database Management Systems (CS570)
• Large Scale XML Data Management (CS5590LD)
• Clinical Epidemiology (BMED5111)
• Evolution (BIOL5519)
• Bioinformatics and Data Analysis (BIOL5525)

• Clinical Bioinformatics (MEDB 5521)

If students have already met the requirements of a course listed above, they may petition to substitute an elective for this course.