Interdisciplinary Studies: Specialization in Bioinformatics (PhD)

Doctor of Philosophy in Interdisciplinary Studies: Specialization in Bioinformatics  (IS_PHDINF)
Unit: School of Interdisciplinary and Graduate Studies (GI)
Affiliated Department: Multidisciplinary
Program Webpage: bioinformatics.louisville.edu/phd

Program Information

The Interdisciplinary PhD Program in Bioinformatics (the Bioinformatics Program) trains students in bioinformatics for careers in research, education, and industry. Bioinformatics is a broad and diverse domain, ranging from management of biological research databases to computational approaches to biomedical modeling and data analysis.

The Bioinformatics Program focuses on those aspects of bioinformatics that reflect the research interests and experience of the Program's faculty. These include basic research in biostatistical methodology, computer science and mathematical modeling with applications to biochemistry, cell biology and molecular biology. The following areas have been identified and named by the Bioinformatics Program faculty to represent the focus application areas of the Program:

  • Biomedical and Natural Sciences
  • Computational Sciences
  • Mathematics and Statistics

Students in the Bioinformatics Program specialize in one of the three focus application areas and graduate with cutting-edge expertise in this area and working knowledge in the other two focus application areas.

To earn the Doctor of Philosophy in Interdisciplinary Studies: Concentration in Bioinformatics, a student is required to successfully complete the following:

  • Core coursework in the focus application areas
  • Required coursework in the student’s area of specialization
  • Elective courses in the student’s area of specialization
  • Qualifying examination
  • Dissertation
  • Presentation and defense of dissertation

Upon successful completion of the written and oral portions of the qualifying examination, the examination committee will recommend acceptance into PhD candidacy. Successful completion of the dissertation and its presentation and defense is established by the approval of the student's dissertation committee and the approval of the chair of the sponsoring department and the program chair.

Admission Requirements

Applicants for interdisciplinary doctoral programs must present complete admission credentials and have an approved program of study in order to be formally admitted by the School of Interdisciplinary and Graduate Studies.

  • A 3.25 grade point average.
  • Competitive scores on the Quantitative, Verbal, Critical Thinking and Analytical portions of the Graduate Record Exam (GRE).
  • Proof of a Baccalaureate Degree and official transcripts of all undergraduate and graduate course work.
  • International students for whom English is not their primary language must show English language proficiency by one of the following:
    • TOEFL examination score at or above 550 (paper based test and a 5.0 on the TWE test), 213 (computer based test),79 (internet based test)
    • IELTS test score of 6.5 or higher
    • Successfully completing the exit examination for the advanced level of the Intensive English as a Second Language Program at the University of Louisville
    • demonstration of a degree award from an acceptable English language institution.
  • Three letters of recommendation from individuals who are able to comment on the student’s academic abilities and a potential for success in graduate studies.

Programs of Study

Course requirements for the Interdisciplinary PhD Degree Program in Bioinformatics consist of 16 core credit hours (that will be conditional based upon focus area) and 21 credit hours derived from a combination of required courses from a chosen focus area and electives from each of the three focus areas. Students with an appropriate background in the biomedical and natural sciences may petition to substitute a course in either the Computational Sciences or Mathematics and Statistics focus for the core course BIOC 545 and a corresponding course in either the Computational Sciences or Mathematics and Statistics, thus maintaining 16 core credit hours. Following acceptance into a focus area, students will be required to complete three courses totaling at least nine hours from the declared focus area. At least four additional elective courses (12 credit hours) will be selected from available elective courses, with the provision that two elective courses must be selected in each of the other two focus areas. The Program of Study will be determined by the student and approved by both an advisor residing in a declared focus area department and the Executive Committee. The following tables list the required courses for the core as well as the required and elective courses in each of the focus areas. Students must accumulate at least nine (9) credit hours of dissertation.  

Good standing requires that the student maintain a minimum 3.0 grade point average. Upon successful completion of the written and oral portions of the qualifying examination, the examination committee will recommend acceptance into PhD candidacy. Successful completion of the dissertation and its presentation and defense is established by the approval of the student’s dissertation committee and the approval of the chair of the sponsoring department and the program chair.

Core Course Work16
Biochemistry I 1,2,3
Responsible Conduct of Research: Survival Skills and Research Ethics 1
Cell Biology
Special Topics in Psychology 1
Introduction to Bioinformatics 1
Statistics for Bioinformatics
Focus Area & Electives (see lists below)21
Focus Area (minimum three courses) 4
Electives (minimum four courses) 4
Dissertation9
Minimum Total Hours46

Focus Area Electives

Elective Courses in Mathematics and Statistics
MATH 505Introduction to Partial Differential Equations3
MATH 507Fourier Analysis3
MATH 561Probability3
PHYS 565Computational Physics3
PHYS 625Statistical Mechanics3
MATH 636Mathematical Modeling II3
PHST 661Probability3
PHST 662Mathematical Statistics3
MATH 562Mathematical Statistics3
MATH 667Statistical Inference3
MATH 670Introduction to the Stochastic Calculus3
MATH 681Combinatorics and Graph Theory I3
MATH 682Combinatorics and Graph Theory II3
PHST 682Multivariate Statistical Analysis3
PHST 691Bayesian Inference and Decision3
PHST 710Advanced Statistical Computing I3
PHST 711Advanced Statistical Computing II3
PHST 724Advanced Clinical Trials3
PHST 725Design of Experiments3
PHST 762Advanced Statistical Inference3
PHST 780Advanced Nonparametrics3
PHST 781Advanced Linear Models3
PHST 782Generalized Linear Models3
Elective Courses in Biomedical and Natural Sciences
BIOL 542Gene Structure and Function 3
BIOL 569Evolution3
BIOC 680Biomolecular Interactions2
BIOC 611Advanced Techniques in Biochemistry and Molecular Biology4
ASNB 614Molecular Neuroscience4
BIOC 647Advanced Biochemistry II 14
CHEM 647Advanced Biochemistry II4
CHEM 648Systems Biochemistry: Principles and Practices3
CHEM 652Independent Study1-3
BIOC 661Molecular Mechanisms of Toxicology3
BIOC 668Molecular Biology and Genetics4
CHEM 684Biophysical Chemistry3
Elective Courses in Computational Sciences
CECS 535Introduction to Databases3
CECS 619Design and Analysis of Computer Algorithms3
CECS 622Simulation and Modeling of Discrete Systems3
CECS 627Digital Image Processing3
CECS 628Computer Graphics3
CECS 629Distributed System Design3
CECS 630Advanced Databases3
CECS 632Data Mining3
CECS 641Medical Imaging Systems3
CECS 645Advanced Artificial Intelligence3
CECS 646Intelligent Systems3