203 Biocomputing Algorithms (3 units) Winter
Instructor(s): R. Hernandez 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: Lecture, Laboratory, Project
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.
209 Statistical Analysis of Microarray Data (1 units) Spring
Instructor(s): M. Segal
This course offers students a series of weekly lectures detailing methods for the analysis of microarray data. After reviewing microarray technology, a range of statistical techniques corresponding to frequently encountered research questions and study design are illustrated and evaluated. Tools for effecting such analyses are also described.
219 Special Topics in Bioinformatics (3 units) 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): R. Hernandez
Presentation and discussion of bioinformatics and medical informatics research topics.
221 Informatics Rotation (1 - 8 units) Fall, Winter, Spring
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.
224 Graduate Research Opportunities Seminar (1 units) Fall, Winter
Instructor(s): R. Hernandez
Restrictions: First year BMI students. Activities: Seminar
This course offers 1st year students a series of weekley presentations of the research interests of the BMI basic science faculty. The purpose is to acquaint new graduate students with research projects and opportunities in faculty labs. The course is modeled after PSPG 225 A&B.
225 Research Project (1 - 8 units) Fall, Winter, Spring
Restrictions: MS students only. Activities: Project
A significant, planned, indepndent research project in collaboration with research advisor, and designed to make a practical contribution to the field of informatics. Final report fulfills requirement for MS degree.
250 Research (1 - 8 units) Fall, Winter, Spring
For PhD students working with research advisor in preparation for oral qualifying exam.
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.