CBIO552 Cancer Biology (Fall; Graded; 4 units)
Cancer Biology is a core course in the Cancer Biology Graduate Program. The primary goal of this course is to familiarize the student with the concepts that serve the foundation for our current view of cancer as a genetic disease. Materials will be drawn primarily from the textbook but will be supplemented with readings from current literature to highlight recent develops in the field. Major topics to be covered include: the multistep model of carcinogenesis, the molecular basis of cancer, cancer detection and diagnosis, and cancer therapeutics.
CBIO553 Advanced Topics in Cancer Biology (Spring; Graded; 4 units)
This course utilizes both lectures and discussions focused on seminal findings in the field and classic fundamental research papers in cancer biology. The emphasis is on the development of skills in data analysis and interpretation, proposal writing, and oral presentation. Through this course the student should be familiar with seminal findings and classic fundamental research in cancer biology, as well as, modern approaches and methods used to address timely areas in cancer biology.
CBIO561 Clinical Cancer Biology Experience (Spring; Graded; 2 units)
Students will learn about the most common types of cancer and the clinical disciplines that are responsible for diagnosing and treating patients with cancer. The course will be focused around a series of lectures by clinicians on common types of cancer. Additionally, students will be responsible for arranging a total of 12 hours of clinical experience with the assistance of the MDs teaching the lectures. Finally, students will select from a variety of multidisciplinary case discussion conferences (tumor board) in the major clinical subspecialties and attend at least two of those conferences.
CBIO595C Cancer Biology Colloquium (Fall, limited to CBIO students; Graded; 1 unit)
This course will give Cancer Biology graduate students and Cancer Biology faculty an opportunity to effectively communicate research findings and journal articles.
CBIO596H Cancer Biology Seminar Series (Fall, Spring; Graded; 1 unit)
University faculty, national and international invited speakers present cancer-related research seminars for this series. Basic and clinical faculty, postdoctoral fellows, graduate students, and research staff attend this seminar series.
BIOS 576A Biostatistics (Fall, Spring; Graded; 3 units)
This course introduces biostatistical methods and applications, and will cover descriptive statistics, probability theory, and a wide variety of inferential statistical techniques that can be used to make practical conclusions about empirical data. Students will also be learning to use a statistical software package (Stata, SAS or R). (Contact Grad Coordinator for information on registering for this course.)
IMB 521 Scientific Grantsmanship (Spring; Graded; 2 units)
An interactive graduate-level course focused on written scientific communication and research integrity/ethics. The writing portion of the course is developed with a particular emphasis on NIH-style grant writing to develop the necessary skills to develop and write fellowship and grant applications. Students will work together with faculty and in peer groups to develop scientific hypotheses, aims, and research plans. The students will develop an NIH-style research proposal through the course of the semester. The student will develop skills necessary to for successful scientific writing.
CBIO900 Research (Fall, Spring)
Individual research, not related to thesis or dissertation preparation, by graduate students
CBIO920 Dissertation (Fall, Spring)
Research for doctoral dissertation (whether library research, laboratory or field observation or research, artistic creation, or dissertation writing).
EPID576A Biostatistics (other statistic courses are acceptable with Program Director approval)
This course introduces biostatistical methods and applications, and will cover descriptive statistics, probability theory, and a wide variety of inferential statistical techniques that can be used to make practical conclusions about empirical data. Students will also be learning to use a statistical software package (STATA).