203 Biocomputing Algorithms (4 units) Winter
Instructor(s): A. Sali Prerequisite(s): Students are expected to have programming competence in a language such as Python, C, C++, or Fortran. Students should also posses a basic knowledge of statistics (undergrad. level).
Restrictions: For all iPQB students and Bioengineering students. Others require instructor approval. Activities: Direct - Lecture, Student - Lecture
Introduction to computational issues and methods used in the field of bioinformatics and computational biology. This course emphasizes the implementation, analysis, and validation of methods. It is about attacking computational problems in biology, not expert use of existing tools. Areas addressed include analytical thinking, problem decomposition, and algorithm design and implementation. Assignments will focus on the design and implementation of key bioinformatics algorithms.
206 Statistical Methods for Bioinformatics (4 units) Fall
Instructor(s): K. Pollard Prerequisite(s): Upper division course work in biological sciences including knowledge of proteins and protein structure, computer literacy.
Restrictions: None. Activities: Lecture, Project
Broad survey of bioinformatics with accompanying assignments. Topics covered include genomics, database searching, family/super-family analysis, structural genomics, complex systems, genetic circuits, and protein-protein interactions.
208 Computational Evolutionary Genomics (3.5 units) Winter
Instructor(s): R. Hernandez Prerequisite(s): BIO MD INF 206 or other bioinformatics background with instructor approval.Familiarity with programing using the R statistical package (understanding of basic loops, ability to define variables, write functions, and perform basic statistical tests).
Restrictions: Programming experience helpful but not required. Activities: Lecture, Laboratory
In this course we will take an evolutionary approach toward understanding patterns of genetic variation, focusing on computational methods commonly implemented in population and comparative genomics. We will consider the role of evolutionary processes in shaping patterns of human disease susceptibility. Each week we will read papers from the literature and discuss/implement their computational methods.
219 Special Topics in Bioinformatics (3 units) Fall, Spring
Instructor(s): Staff Prerequisite(s): None.
Restrictions: Priority given to first-year graduate students. Activities: Lecture, Conference, Independent Study
Each course offering will focus on the literature of a current important area of Bioinformatics. Students will be expected to read assigned papers critically before class and to present and discuss papers in class. Students will also be expected to write and present a brief research proposal based upon their reading. Topics in Molecular, Cellular, developmental, systems, and computation biology will be covered in separate course offerings.
220 Informatics Seminar (1 units) Fall, Winter, Spring
Instructor(s): K. Pollard Prerequisite(s): None.
Restrictions: n/a Activities: Lecture
This course consists of presentation and discussion of research in quantitative biology and bioinformatics by outside speakers.
221 Informatics Rotation (1 - 8 units) Fall, Winter, Spring, Summer
Instructor(s): Staff Prerequisite(s): None
Restrictions: None Activities: Laboratory
An introduction to the specific research currently underway within a faculty member's laboratory.
223 Critical Topics in Biomedical Informatics (1 units) Fall, Winter, Spring
Instructor(s): B. Shoichet Prerequisite(s): None.
Restrictions: None. Activities: Seminar
Critical review of published scientific papers from scholarly journals, including comprehension, analysis and evaluation of published scientific data.
250 Research (4 - 8 units) Fall, Winter, Spring, Summer
Instructor(s): Staff Prerequisite(s): None
Restrictions: None Activities: Direct - Project
In this course, students will work together with a primary research advisor to select a research question and design a project workplace that will be carried out by the student. Through this activity, the student will gain experience in research strategy, learn techniques associated with modern biomedical research, and practice how to interpret results. At the conclusion of the course, the student will present on their progress.
299 Dissertation (0 units) Fall, Winter, Spring
Instructor(s): Staff Prerequisite(s): Advancement to candidacy.
Restrictions: BMI students only.
For students advanced to candidacy working on their dissertation.