Required Courses

PHCO 701—Introduction to Molecular Pharmacology.
A one-semester course on general principles of pharmacology

PHCO 702—Principles of Pharmacology and Physiology.
A one semester course that focuses on advanced pharmacological and physiological principles of drug action. (Not required for MSTP students)

1 of the following courses, designed to ensure students have a foundation in some form of quantitative data analysis:

BBSP 710, 2 credits. Statistics for Lab Scientists. BBSP710 is ideal for wet bench scientists beginning their 2nd or 3rd year in graduate school. The course centers round the use of Prism as a platform to carry out different forms of statistical analyses that are broadly relevant to the experimental biological sciences.

BIOS 511, 4 credits. Introduction to Statistical Computing and Data Management. Permission of instructor required for nonmajors. Introduction to use of computers to process and analyze data, concepts and techniques of research data management, and use of statistical programming packages and interpretation. Focus is on use of SAS for data management and reporting.

BIOS 512, 3 credits. Data science basics. Students will gain proficiency with R, data wrangling, data quality control and cleaning, data visualization, exploratory data analysis, with an overall emphasis on the principles of good data science, particularly reproducible research. The course will also develop familiarity with several software tools for data science best practices, such as Git, Docker, Jupyter, Make, and Nextflow.

BIOS 611, 4 Credits. Introduction to Data Science. Topics will include gaining proficiency with R and Python, data wrangling, data quality control and cleaning, data visualization, exploratory data analysis, and introductory applied optimization, with an overall emphasis on the principles of good data science, particularly reproducible research. Some emphasis will be given to large data settings such as genomics or claims data. The course will also develop familiarity with software tools for data science best practices, such as Git, Docker, Jupyter, and Nextflow.

BCB 720, 3 Credits. Introduction to Statistical Modeling. A semester-long course taught each fall that introduces foundational statistical concepts and models that motivate a wide range of analytic methods in bioinformatics, statistical genetics, statistical genomics, and related fields. It is an intensive course, packing a year’s worth of probability and statistics into one semester. It covers probability, common distributions, Bayesian inference, maximum likelihood and frequentist inference, linear models, logistic regression, generalized and hierarchical linear models, and causal inference, plus, typically, additional topics from guest lecturers.

Students who have already taken a graduate-level course in statistics may opt out of this requirement with approval from the DGS. Please send your request, the course syllabus, and evidence of your grade to our student services manager.

PHCO 730—Recent Advances in Pharmacology.
A presentation-based course geared towards techniques and critical evaluation of the literature. Each student will present once during the semester

PHCO 732—Grant Writing Workshop.
A one-semester course designed to help students develop their grant writing skills and prepare for their qualifying exams.

2 Electives — Any graduate-level 1, 2 or 3-credit course, in any scientific discipline, will satisfy this requirement. Elective courses must total at least 4 credit hours.

CBPH 895 – Refresher Course on Responsible Conduct of Research (RCR).
Course Director: Jay Brenman, PhD
Fourth year students take a short mini-course with face to face faculty led discussions regarding issues that arise while responsibly conducting research. This is meant as a “refresher” for more experienced students that have had 1st year BBSP RCR exposure previously and includes NIH suggested topics and readings. Case studies and hypothetical situations involving potential scenarios confronting graduate students will be covered. These topics include: mentor and mentee relationships, publication authorship, collaboration, peer review, ethical use of human and animal subjects, conflicts of interest, intellectual property, plagiarism, data acquisition and data processing. 6 classes for a total of 9 contact hours. Fall semester: Brenman and Faculty.