PhD in Informatics with Emphasis in Bioinformatics
The following is a brief synopsis of the general degree requirements; please see the Informatics Institute web site for complete details:
- Students must take required and area courses.
- Students must pass a qualifying examination.
- Students must present at least one institutional seminar annually.
- Students are required to complete a comprehensive exam, which includes written and oral elements, within a specified time frame.
- Students must pass a comprehensive examination at least 7 months before their scheduled defense.
- Students must submit and defend a dissertation describing the results of successful and original research in one of the branches of informatics.
- To show research progress, students are expected to be working toward presenting at conferences and publishing in peer-reviewed journals based on their informatics research.
All students must have at least 72 credit hours at the graduate level, of which 15 credits must be at the 8000-level not including research, problems, lab rotations, or seminar. Transferring credits will be at the recommendation of the student's doctoral committee and the approval of the MUII Curriculum Committee.
|REQUIRED CORE COURSES - BIOINFORMATICS EMPHASIS AREA|
|INFOINST 7002||Introduction to Informatics||3|
|INFOINST 7010||Computational Methods in Bioinformatics||3|
|REQUIRED METHODS COURSES (9 Credit Minimum)|
|INFOINST 8810||Research Methods in Informatics||3|
|STAT 7510||Applied Statistical Models I||3|
|Student must choose one additional 3-credit methods course with doctoral committee approval.|
|LAB ROTATIONS AND SEMINAR|
|INFOINST 8087||Seminar in Informatics (Must be enrolled each semester)||0.5-1|
|INFOINST 8088||Lab Rotations in Informatics||2|
|INFOINST 8090||Dissertation (pre-candidacy) Research in Informatics||1-99|
|INFOINST 9090||Dissertation (post-candidacy) Research in Informatics||1-99|
|AREA COURSE ELECTIVES (15 credits)|
|AN_SCI 7001||Topics in Animal Science (Molecular Evolution)||1-4|
|CMP_SC 7380||Database Management Systems I||3|
|CMP_SC 7740||Interdisciplinary Introduction to Natural Language Processing||3|
|CMP_SC 8370||Data Mining and Knowledge Discovery||3|
|CMP_SC 8630||Data Visualization||3|
|ECE 7270||Computer Architecture||4|
|ECE 7590||Computational Neuroscience||4|
|ECE 8320||Nonlinear Systems||3|
|ECE 8570||Neural Dynamics and Communication||3|
|ECE 8580||Machine Learning in Neuroscience||3|
|GEOG 7620||Biogeography: Global Patterns of Life||3|
|GEOG 7710||Spatial Analysis in Geography||3|
|GEOG 7810||Landscape Ecology and GIS Analysis I||3|
|GEOG 7840||Geographic Information Systems I||3|
|GEOG 7860||Advanced Remote Sensing||3|
|GEOG 7940||Advanced Geographic Information Systems (GIS II)||3|
|GEOG 8840||Seminar: Applied Remote Sensing|
|GEOG 8902||Topics in Geography-Biological/Physical/Mathematical||1-3|
|HMI 7410||Introduction to the US Health Care System||3|
|HMI 8435||Information Security, Evaluation and Policy||3|
|HMI 8437||Data Warehousing and Data/Text Mining for Health Care||3|
|HMI 8441||Biomedical and Health Vocabularies and Ontologies||3|
|HMI 8443||Enterprise Information and Solutions Architecture for Strategic Healthcare Operations||3|
|HMI 8460||Administration of Health Care Organizations||3|
|HMI 8461||Managing Human Resources in Health Care Organizations||3|
|HMI 8478||Knowledge Management in Health Care||3|
|HMI 8524||Health Economics||3|
|HMI 8565||Health Care Ethics||3|
|HMI 8571||Decision Support in Health Care Systems||3|
|HMI 8573||Decision Making for Health Care Organizations||3|
|HMI 8610||Consumer Health Informatics||3|
|IMSE 8810||Human Factors||3|
|INFOINST 8005||Applications of Bioinformatics Tools in Biological Research||3|
|INFOINST 8085||Problems in Informatics||1-6|
|INFOINST 8150||Integrative Methods in Bioinformatics||3|
|INFOINST 8190||Computational Systems Biology||3|
|INFOINST 8310||Computational Genomics||3|
|INFOINST 8870||Knowledge Representation in Biology and Medicine||3|
|IS_LT 9410||Seminar in Information Science and Learning Technology||1-3|
|NURSE 9460||Theories and Interventions in Health Behavior Science||3|
|PTH_AS 7450||Precision Medicine Informatics||3|
Qualifying Exam Process
Students are expected to take the qualifying exam by the end of their third semester in the program. The exam will be based on their previous coursework, lab rotation experience, and one-page research statement. For more information on qualifying exam procedures, please see the MUII student handbook.
Comprehensive Exam Process
The comprehensive exam consists of two parts - the written portion, comprised of an R01 research proposal, and the oral exam. For more information on the comprehensive exam process, please see the MUII student handbook.
Dissertation Defense Process
The doctoral dissertation defense must be scheduled no sooner than seven months after successful completion of the comprehensive exam. The dissertation must be written on an informatics subject approved by the candidate's doctoral program committee, must embody the results of original and significant investigation, and must be the candidate's own work. Please refer to the MUII student handbook for additional information.
Admission Contact Information
MUII Staff (mailto: email@example.com)
241 Engineering Building West
Columbia, MO 65211-2060
Informatics Institute (MUII) website: https://muii.missouri.edu
Fall deadline: The deadline for Fall admission is March 1. However, to be considered for departmental and Graduate School fellowships and assistantships, applications should be submitted by January 15.
- Preferred GPA: 3.3 out of 4.0
- Preferred GRE scores*:
|When did you take the GRE?||Verbal + Quantitative||Analytical|
|Prior to August 1, 2011||1200||3.5-4.0|
|On or After August 1, 2011||309||3.5-4|
or a preferred GMAT score of 570
- Preferred TOEFL OR IELTS scores**:
|Internet-based test (iBT)||Paper-based test (PBT)|
All Required Documents
Students are required to send ALL required application materials through the Office of Graduate Schools on-line application system. To begin your application, please see the ApplyYourself website.
- Curriculum Vitae
- Statement of Purpose, which should include a summary of why the applicant is interested in pursuing an advanced informatics degree, a brief description of your previous research experiences, the specific area of informatics you are interested in pursuing, and your future career goals and plans in the informatics field.
- GRE/GMAT scores. Use institution code 6875. The departmental code is not required.
- TOEFL/ELTS scores for international applicants, if required.
- Three letters of recommendation from faculty or supervisors who can evaluate the applicant’s credentials and potential to become successful in the area of informatics.
- Scanned copies of transcripts from each college and university attended. If accepted, applicants will be required to have official copies of their transcripts sent directly from the institution to the Graduate School.
Applicants are encouraged to submit representative publications in informatics, if available.
Exceptional Funding Opportunities - Biomedical Big Data Science Pre-doctoral Training
Funded by NIH T32 (2016-2021)
MU Informatics Institute (MUII) is recruiting SIX top-notch trainees to pursue PhD degree in Informatics through an interdisciplinary training team. Students from basic sciences, life sciences, medicine, and computing disciplines are welcome to apply. Our unique training includes: (1) personalized training modules from core courses of the MS degree in Data Science and Analytics program, Big Data courses from Computer Science, and biomedical informatics courses from MUII, which will expose trainees to the basic concepts, ethics, and working knowledge in Big Data Science; (2) a problem-based learning curriculum in pre-doctoral-level Big Data-related courses, such as Mining Massive Data Sets for Biomedical Applications, designed to foster a team science approach to problem-solving; (3) a student-driven journal club/seminar series, in which students are offered opportunities to present research, pose questions, and receive feedback from peers and mentors. Our interdisciplinary components include (1) required tri-lab rotations to introduce students to animal/veterinary medical research, human medical research, computing/statistical methodologies, and health communications; (2) development of rigorous and reproducible open-source Big Data analytics tools, which will be assessed by the One Health research community after arduous testing; and (3) creation of an Individual Development Plan based on each trainee's background and career goal prior to joining the program. These positions are open to permanent residents and US citizens only. Women and minority students are encouraged to apply.
Please contact the project director Dr. Chi-Ren Shyu at ShyuC@missouri.edu for inquiries.