This course introduces all major aspects of cellular structure and function. It specifically covers cytoplasmic membranes, protein trafficking, cellular signaling and cell proliferating mechanisms.

This course allows for research faculty mentors to present potential dissertation projects available for BMS PhD students to undertake upon choosing a dissertation lab. Research rotations will also be completed in this course.

This course allows for research faculty mentors to present potential dissertation projects available for BMS PhD students to undertake upon choosing a dissertation lab. Research rotations will also be completed in this course.

This course allows for BMS PhD students to complete a summer research rotation with BMS faculty to assist with choosing a dissertation advisor.

BMSP 7770 is for first year PhD students in the Biomedical Sciences Graduate Program. This course will provide PhD students with a basic knowledge of physiology organ systems (neuroscience, kidney, GI, cardiovascular, reproduction, endocrinology, respiration), highlighting the pathophysiology of disease mechanisms, and integrates pharmacology and sex differences into the curriculum. The course is team-taught, and faculty emphasize their particular research field. Student performance will be assessed with four examinations. All lectures have learning objectives, and exams will cover the material outlined in the learning objectives and covered in class. No textbook is required but some may be recommended.

Course may be repeated up to unlimited credit hours.

Course may be repeated up to unlimited credit hours.

This course will provide the students with an overview in the field of sports medicine. The course focuses on the basic information and skills important to the recognition, care, prevention, and preliminary rehabilitation of athletic injuries. The course will explore medical providers involved in total athlete care, provide terminology associated with sports medicine, and discover the human body systems as they pertain to sports medicine.

Discuss common non-traumatic injuries in young athletes. Categorize non-traumatic injuries. Analyze athlete pre-participation assessments in terms of specific non-traumatic injury categories. Differentiate among common non-traumatic injuries found in secondary and post-secondary level athletics. Identify proper protocol for assessing critical illnesses and providing care for an injured athlete. Analyze the implementation of guidelines for continuation within the activity by the injured athlete. Understand of ergonomic theory behind safety equipment. Determine the proper protective equipment for an athlete based on sport, athlete age and size. Describe the preparation needed for athletic coverage. Analyze recent incidents of non-traumatic injuries in secondary and collegiate athletics. Identify the key components of an Emergency Action Plan. Review and critique an existing Emergency Action Plan. Develop an Emergency Action Plan.

This course offers a comprehensive study of the physical, nutritional, and therapeutic methods of injury recovery while holding a focus on the needs of athletes who want to improve performance within their sport.

This course will explore the process of developing and maintaining a sports medicine program that fully addresses the continuum of care for athletes within an institution or organization at the collegiate and secondary levels. Students will discover the components of a comprehensive athletic healthcare program including: health and safety policies and procedures, roles and responsibilities of involved healthcare providers, and best practices of sports medicine.

In this course, students will study IRB relations and regulations, discuss the required elements in a clinical research contract and the responsibilities of the clinical researcher, identify effective use of research personnel, and develop negotiating skills to facilitate support for clinical research. The course will also encompass the principle of randomization and “intention-to-treat” analysis in experimental studies, integration of clinical trials and lab support, specimen collections and laboratory problem-based learning. A researcher/clinician centric insight into the logistics of technology transfer and intellectual property (IP) development will be studied. The practical aspects of technology transfer in an academic context will be investigated. Discussed topics will include local academic tech transfer policy, related procedures and available resources. Career pathways and opportunities open to the clinical researcher in the academic and private sector will be explored and discussed.

Study of molecular medicine.

Course may be repeated up to unlimited credit hours.

Goals/Mission: To develop an understanding of biomedical informatics, the biomedical data, the practice modern medicine, conduct modern biological research, and health sciences education with information technology. Prerequisites: Students should have a basic understanding of intermediate mathematics. Designation: This course is for graduate students and advanced undergraduate students

Goals/Mission: The goal is to provide a comprehensive orientation to data science using SQL, R, Phyton, and programs with application to biomedical informatics Prerequisites: The course does not require prior programming knowledge. Designation: This course is for graduate students and advanced undergraduates

Goals/Mission: To develop an understanding of the integrated behavior of random variables multivariate data sets using R/ Python with application to complex biomedical data. Prerequisites: Students should have a basic understanding of statistics, multivariable calculus, and linear/matrix algebra. Designation: This course is for graduate students and advanced undergraduate students.

Goals/Mission: To develop an understanding of the advanced approaches of bioinformatics and its application. Prerequisites: Students should have a basic understanding of biomedical informatics and statistics. Designation: This course is for graduate students.

Goals/Mission: To develop a comprehensive understanding of modeling for pattern recognition in data and utilizing these models to predict future data. This course is for graduate students and advanced undergraduate students with permission of instructor.

The Biomedical Informatics Workshop is designed to promote reading, writing, oral presentation skills, and critical analysis of biomedical data, and research related to are a key tool for critically appraising articles and keeping up to date with the current literature. BIMI 7210 Workshop I - IV (1 credit hour) allows credit for participation in these journal clubs.

The first two years are generally devoted to coursework and research. In conjunction with the course work in the first year, students rotate in 6-8 week blocks through three of the division’s participating research laboratories of the student’s choice. BIMI 7220 Research Methods allows 2 credit hours per rotation. Subsequent years focus on independent research that culminates in a dissertation. Students accepted into the BMS BMI track are required to join faculty in the Division of Biomedical Informatics and Genomics, but may consider one of other faculty outside of the Division for committee members or co-mentors (with approval of the Division Chief).

The first two years are generally devoted to coursework and research. In conjunction with the course work in the first year, students rotate in 6-8 week blocks through three of the division’s participating research laboratories of the student’s choice. BIMI 7230 Research Methods allows 2 credit hours per rotation. Subsequent years focus on independent research that culminates in a dissertation. Students accepted into the BMS BMI track are required to join faculty in the Division of Biomedical Informatics and Genomics, but may consider one of other faculty outside of the Division for committee members or co-mentors (with approval of the Division Chief).

Goals/Mission: To develop an understanding of programming and high-performance computing techniques in data science with cloud computing. This course is for graduate students and advanced undergraduate students with permission of instructor.

Goals/Mission: To understand how to use and analyze high-throughput genomics and omics data in biomedical informatics. The course covers various high-throughput omics data, including genomics, transcriptomics, and proteomics data, as well as their data analysis methods and applications in biological and disease studies. Designation: This course is for graduate students and advanced undergraduate students.

To develop an understanding of various algorithm design techniques, such as exhaustive search, greedy search, divide-and conquer, dynamic programming, graph-based algorithms, and randomized algorithms, as well as various computational problems in biomedical informatics, such as sequence alignment, genome arrangement, motif finding, and peptide identifications. These problems are used as examples to demonstrate how to solve biomedical problems by mathematical modeling and algorithm design. Designation: This course is for graduate students and advanced undergraduates.

The first two years are generally devoted to coursework and research. Subsequent years focus on independent research that culminates in a dissertation. Students accepted into the BMS BMI track are required to join faculty in the Division of Biomedical Informatics and Genomics, but may consider one of other faculty outside of the Division for committee members or co-mentors (with approval of the Division Chief). BIMI 7990 Directed Independent Study (3 credit hours) allows credit for independent research under the direction of a mentor or co-mentor in the Division of Biomedical Informatics and Genomics.

Goals/Mission: Journal clubs are a key tool for critically appraising articles and keeping up to date with the current literature. Designation: This course is for graduate students only.

Goals/Mission: To develop an understanding of the advanced approaches of computational biology, and their application. Designation: This course is for graduate students and advanced undergraduate students.

Goals/Mission: To develop an understanding of the advanced approaches with algorithms in representation learning, generative adversarial networks, and their application to imaging multi-omics data. Designation: This course is for graduate students and advance undergraduate students.

Goals/Mission: The goal is to develop a deeper understanding of a research field in biomedical informatics and gain capability to design a conceptual framework, conduct data analysis , and write a dissertation proposal. Designation: This course is for graduate students