Motivation
A Ph.D. in Bioinformatics Data Science will train the next-generation of researchers and professionals who will play a key role in multi- and interdisciplinary teams, bridging life sciences and computational sciences. Students will receive training in experimental, computational and mathematical disciplines through their coursework and research. Students who complete this degree will be able to generate and analyze experimental data for biomedical research as well as develop physical or computational models of the molecular components that drive the behavior of the biological system.
Degree Requirements (Browse Courses)
Students must complete a minimum of 15 credits of coursework, 6 credits of seminar, 6 credits of research and 9 credits of doctoral dissertation. Students who are admitted directly after a B.S. degree will be required to fulfill the Bioinformatics and Computational Biology M.S. core curriculum by completing an additional 9 credits as prerequisites (for a total of 24 credits) in the following areas: Database Systems, Statistics, and Introduction to Discipline. In addition, if students entering the program with an M.S. degree are lacking equivalent prerequisites, they also will be required to complete courses in these three areas; however, these courses may fulfill the elective requirement in the Ph.D. program, if approved in the program of study.
| Credit Requirements | Credits |
|---|---|
| A. Bioinformatics Data Science | 9 |
| B. Prerequisites | up to 9 |
| C. Electives | 6 |
| D. Seminar | 6 |
| E. Research | 6 |
| F. Doctoral Dissertation | 9 |
| Total Number of Required Credits | 36-45 |
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A. Bioinformatics Data Science Courses 9 credits Bioinformatics (select one) BINF644 Bioinformatics 3 CISC636 Computational Biology and Bioinformatics 3 Data Science – Systems Biology (select one) BINF694 Systems Biology I:
Experimental Techniques and Bioinformatics Analysis of Omics Data3 BINF695 Computational Systems Biology:
Computational Modeling of Processes in Cells and Biological Systems3 Data Science – Data Analytics (select one) NURS/HLTH844 Population Healthcare Informatics 3 CISC681 Introduction to Artificial Intelligence 3 CISC683 Introduction to Data Mining 3 CISC684 Introduction to Machine Learning 3 BINF667-013 Introduction to Data Science 3 BINF667-010 Applied Machine Learning 3 BINF667-012 Big Data Analytics in Biomedicine and Health 3 B. Prerequisites 3-9 credits Introduction to Discipline (select one) BISC609 Molecular Biology of the Cell 3 BISC654 Biochemical Genetics 3 PLSC667 Applications of Genome Science:From Microbes to Mammals 3 BINF690 Programming for Bioinformatics 3 Database (select one) BINF640 Databases for Bioinformatics 3 CISC637 Database Systems 3 Biostatistics (select one) STAT656 Biostatistics 3 STAT611 Regression Analysis 3 C. Elective Courses 6 credits Recommended Electives CISC682 Introduction to Human-Computer Interaction 3 CISC681 Introduction to Artificial Intelligence 3 CISC684 Introduction to Machine Learning 3 BINF685 Modelling and Simulation for Bioinformatics Systems 3 CISC841 Algorithms in Bioinformatics 3 CISC844 Computational Biomedicine 3 CHEG621 Metabolic Engineering 3 ELEG671 Mathematical Physiology 3 EGGG667 Technical and Scientific Writing 3 MAST 607 Writing Papers in Marine Sciences 3 MEEG621 Linear Systems 3 UAPP648 Environmental Ethics 3 UAPP650 Values Ethics and Leadership 3 BUAD840 Ethical Issues in Business Environments – ONLINE 3 BINF0007-012 Data Science with Online Competitions 1 Other Electives ANFS/PLSC671 Paradigms in Cell Signaling 3 BHAN856 Multivariable Biostatistics 3 BINF650 Protein Modifications: Protein Structure and Function 3 BISC602 Molecular Biology of Animal Cells 3 BISC605 Advanced Mammalian Physiology 3 BISC612 Advanced Cell Biology 3 BISC615 Vertebrate Developmental Biology 3 BISC620 Endocrine Physiology 3 BISC625 Cancer Biology 3 BISC656 Evolutionary Genetics 3 BISC671 Cellular and Molecular Immunology 3 BISC679 Virology 3 BISC682 Bacterial Pathogens: Molecular Mechanisms 3 BISC690 Fundamentals of Pharmacology 3 BISC833 Special Topics in Biology 3 CHEG620 Biochemical Engineering 3 CHEM621 Metabolic Engineering 3 CHEM624 Principles of Mass Spectrometry 3 CHEM641 Biochemistry 3 CHEM645 Protein Structure and Function 3 CHEM646 DNA-Protein Interactions 3 CHEM649 Molecular Biophysics 3 CISC621 Algorithm Design and Analysis 3 CISC640 Computer Graphics 3 CISC642 Introduction to Computer Vision 3 CISC650 Computer Networks II 3 CISC675 Object Oriented Software Engineering 3 CISC849 Advanced Topics in Computer Applications 3 CISC879 High Performance Computing and Data Analytics 3 CISC882 Natural Language Processing 3 CISC886 Multi-Agent Systems 3 CISC887 Internet Information Gathering 3 CISC888 Machine Learning 3 CISC 889 Advanced Topics in Artificial Intelligence 3 CPEG/ELEG657 Search and Data Mining 3 CPEG667 Computational & Data Intensive Research Applications & Platforms 3 EGGG667 Technical and Scientific Writing 1 ELEG633 Image Processing 3 ELEG652 Principles of Parallel Computer Architectures 3 ELEG655 High Performance Computing with Commodity Hardware 3 ELEG671 Mathematical Physiology 3 ELEG679 Introduction to Medical Imaging Systems 3 ELEG680 Immunology for Engineers 3 EPID605 Introduction to Epidemiology 3 KAAP602 Data Analysis and Interpretation in Health Sciences 3 KAAP654 Medical Physiology 3 MATH667 Special Topics Topological Data Analysis 3 MAST607 Writing Papers in Marine Sciences 3 MAST616 Methods in Molecular Biology 3 MAST618 Microbial Ecology 3 MAST623 Physiology of Marine Organisms 3 MAST625 Microbial Physiology and Diversity 3 MAST626 Microbial Molecular Genetics 3 MAST634 Marine Molecular Sciences 3 MATH637 Mathematical Techniques in Data Science 3 MATH611 Introduction to Numerical Analysis and Scientific Computing 3 NURS/HLTH844 Population Healthcare Informatics 3 PHIL613 Research Ethics 3 PHIL667 Scientific Methodology and Reproducability 3 PHYT632 Applied Physiology I 3 PLSC644 Physiology of Plant Stress 3 PLSC667 Analytical Plant Genetics 3 STAT608 Statistical Research Methods 3 STAT612 Advanced Regression Techniques 3 STAT615 Design and Analysis of Experiments 3 STAT617 Multivariate Methods 3 STAT619 TimeSeries Analysis 3 STAT621 Survival Analysis 3 STAT670 Introduction to Statistical Analysis I 3 STAT671 Introduction to Statistical Analysis II 3 STAT674 Applied DataBase Management 3 D. Seminar 3 credits Seminar BINF865 Seminar 0-1 E. Research 6 credits Research BINF 868 Research (until Successful completion of preliminary exam) 1-6 BINF 964 Pre-Candidacy (until Successful completion of candidacy exam) 1-6 F. Dissertion 9 credits BINF969 Doctoral Dissertation 1-9
See Course Requirements
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