Bioinformatics Courses

Department of Bioinformatics & Biostatistics, SJTU

General Information

All the course involves lectures, computer exercises and optional written reviews or projects. The final grades will depend on the instructor.

Course Requirements

Student evaluation will be based on data analysis homework assignments and a final project. Students who want to learn the concepts without programming may take the class pass/fail and perform a literature review for a final project.

Courses List

• Algorithms in Computational Biology
  Lecturer: Dr. Liu , Associate Professor
  Course Description: The purpose of this course is to present a representative solutions of computational problems in molecular biology and some efficient algorithms that have been proposed to solve them .



• Advanced Bioinformatics: Sequence and Structure Analysis
  Lecturer: Dr. Chen Haifeng, Associate Professor
  Course Description: This course is a foundation for the undergraduate and graduate student. Features sequence alignment, structure prediction, database searching, molecular dynamics simulation, computer-aided drug design, underlying algorithms, examples in simple numerical terms, tables, and web sources.
  
  
• Linux and Shell Scripting
  Lecturer: Woo Maoying
  Course Description: This is a basic introduction to the Linux operating system and Shell scripting. This course provides students with the knowledge and skills necessary to use any version of Unix. The format of the course consists of lecture and hands-on lab work. It is appropriate for Non-Computer majors.
  
  
• Python & Perl Programming
  Lecturer: Woo Maoying
  Course Description: This course is designed for biologists who already have some programming knowledge, in other languages such as perl or C. What distinguishes this course from general Python introductory courses, is however the important focus on biological examples that are used throughout the course, as well as the suggested exercises drawn from the field of biology. The second half of the course describes the Biopython (http://www.biopython.org/) set of modules. This course can be considered a complement to the Biopython tutorial, and what's more often refers to it, by bringing practical exercises using these components.
  
  
• R Language and Microarray Analysis
  Lecturer: Woo Maoying
  Course Description: This course is a foundation for the undergraduate and graduate student. Features sequence alignment, structure prediction, database searching, molecular dynamics simulation, computer-aided drug design, underlying algorithms, examples in simple numerical terms, tables, and web sources.
  
  
• Computational Systems Biology
  Lecturer: Dr. Wang Zhuo
  Course Description: This course is a foundation for the undergraduate and graduate student. Features sequence alignment, structure prediction, database searching, molecular dynamics simulation, computer-aided drug design, underlying algorithms, examples in simple numerical terms, tables, and web sources.