Bioinformatics - Master of Science

The degree requirements include 30-31 graduate credit hours. The degree has two tracks, one for students with non-computing background and another for students with Computer Science background. The requirements for each track are structured as follows.

Track: Non-Computing Background

Course List
Prefix	Title	Credits
Required Courses
Core Courses
BIOL 550	Special Topics (Command Line Bioinformatics)	3
A ST 505	Statistical Inference I	4
C S 453	Python Programming I	3
BIOL 550	Special Topics (R for ecological sciences)	3
or C S 458	R Programming I
C S 509	Bioinformatics Programming	3
C S 508	Introduction to Data Mining	3
or C S 519	Applied Machine Learning I
Elective Courses (2 from the following list)		6
C S 462	Object Oriented Programming Transition	3
C S 516	Bioinformatics	3
C S 586	Algorithms in Systems Biology	3
GENE 452	Applied Bioinformatics	3
or BIOL 566	Advanced Bioinformatics and NCBI Database
A ST 550	Special Topics (Statistical bioinformatics course)	1-4
A ST 550	Special Topics (Current topics in bioinformatics - open issues)	1-4
Master's Project/Thesis/Internship ¹		6
C S 598	Master's Project	6
or C S 599	Master's Thesis
Total Credits		31

¹: A student can write a thesis (C S 599 Master's Thesis), undertake a research project (C S 598 Master's Project), or participate in an internship related to the degree. In each case, six graduate credits are required and a written approval from the student's advisor must be obtained before the student undertakes this part of the study. For students with thesis or project, the students are required to sustain a final exam, covering the thesis/research project.
²: One course to cover prerequisites to enter GENE 315 Molecular Genetics and BCHE 341 Survey of Biochemistry is required.

Track: Computer Science Background

Course List
Prefix	Title	Credits
Required Courses ²
C S 508	Introduction to Data Mining	3
C S 509	Bioinformatics Programming	3
C S 570	Analysis of Algorithms	3
C S 586	Algorithms in Systems Biology	3
C S 581	Advanced Software Engineering	3
Select one from the following:		3
C S 516	Bioinformatics	3
GENE 452	Applied Bioinformatics	3
BIOL 566	Advanced Bioinformatics and NCBI Database	3
Elective Courses (2 from the following list)		6
A ST 505	Statistical Inference I	4
A ST 506	Statistical Inference II	3
BCHE 546	Biochemistry II	3
BCHE 649	Topics in Biochemistry	1-3
BIOL 474	Immunology	3
BIOL 475	Virology	3
BIOL 478	Molecular Biology of Microorganisms	3
BIOL 490	Neurobiology	3
BIOL 520	Molecular Cell Biology	3
BIOL 566	Advanced Bioinformatics and NCBI Database	3
C S 502	Database Management Systems I	3
C S 505	Artificial Intelligence I	3
C S 516	Bioinformatics	3
C S 521	Parallel Programming	3
C S 575	Artificial Intelligence II	3
C S 582	Database Management Systems II	3
GENE 452	Applied Bioinformatics	3
GENE 486	Genes and Genomes	3
MOLB 542	Biochemistry I	3
MOLB 546	Biochemistry II	3
MOLB 590	Discussions in Molecular Biology	1
Master Thesis/Project/Internship ¹		6
C S 599	Master's Thesis	1-6
or C S 598	Master's Project
Total Credits
Total Credits		30

¹: A student can write a thesis (C S 599 Master's Thesis), undertake a research project (C S 598 Master's Project), or participate in an internship related to the degree. In each case, six graduate credits are required and a written approval from the student's advisor must be obtained before the student undertakes this part of the study. For students with thesis or project, the students are required to sustain a final exam, covering the thesis/research project.
²: One course to cover prerequisites to enter GENE 315 Molecular Genetics and BCHE 341 Survey of Biochemistry is required.

Degree Road Map

For students with non-computing background
- Semester 1: Command Line bioinformatics, C S 458 R Programming I, A ST 505 Statistical Inference I
- Semester 2: C S 453 Python Programming I, one elective course, C S 509 Bioinformatics Programming
- Semester 3: C S 508 Introduction to Data Mining, Masterʼs project/thesis/internship (3 credits), one elective
- Semester 4: Masterʼs project/thesis/internship (3 credits)
For students with Computer Science background
Semester 1: The course to cover the prerequisites to enter GENE 315 Molecular Genetics and BCHE 341 Survey of Biochemistry, A ST 505 Statistical Inference I, C S 508 Introduction to Data Mining
Semester 2: C S 509 Bioinformatics Programming, GENE 315 Molecular Genetics, BCHE 341 Survey of Biochemistry
Semester 3: Masterʼs project/thesis/internship (3 credits), two electives
- Semester 4: Masterʼs project/thesis/internship (3 credits)

A Suggested Plan of Study for Students (with non-computing background)

It is only a suggested plan of study for students and is not intended as a contract. Course availability may vary from fall to spring semester and may be subject to modification or change.

Plan of Study Grid
Semester 1		Credits
C S 458	R Programming I	3
A ST 505	Statistical Inference I	4
Command Line Bioinformatics		3
	Credits	10
Semester 2
C S 453	Python Programming I	3
C S 509	Bioinformatics Programming	3
Elective Course		3
	Credits	9
Semester 3
C S 508	Introduction to Data Mining	3
Elective Course		3
Master's Project/thesis or internship		3
	Credits	9
Semester 4
Master's project/thesis or internship		3
	Credits	3
	Total Credits	31

A Suggested Plan of Study for Students (with a Computer Science background)

It is only a suggested plan of study for students and is not intended as a contract. Course availability may vary from fall to spring semester and may be subject to modification or change.

Plan of Study Grid
Semester 1		Credits
C S 508	Introduction to Data Mining	3
C S 509	Bioinformatics Programming	3
BIOL 566	Advanced Bioinformatics and NCBI Database	3
	Credits	9
Semester 2
C S 516	Bioinformatics	3
C S 570	Analysis of Algorithms	3
GENE 452	Applied Bioinformatics	3
	Credits	9
Semester 3
C S 581	Advanced Software Engineering	3
C S 586	Algorithms in Systems Biology	3
Elective Course ¹		3
	Credits	9
Semester 4
Master's project/thesis or internship		3
Elective Course ¹		3
	Credits	6
	Total Credits	33