chapman-biol302 / course-info

Bio 302 syllabus etc.

Biology 302: Introduction to Bioinformatics

• Instructor Mike Macpherson mmacpher at chapman
• Meets Tuesday & Thursday, 11:30-12:45 PM, Beckman 203
• Office Hours Von Neumann 102, Monday and Wednesday, 1-3pm or by appt.

Course Description

Prerequisites: BIOL 208 and CPSC 230. Students will learn how to use computer programming techniques to solve problems in biology. Students will learn the structure and capabilities of the Biopython library and will learn how to use how to use it to perform tasks such as automating searches of biological databases, manipulating nucleotide and protein sequences, searching for PCR primers, inferring splicing sites, and investigating DNA mutations. (3 credits)

Course Objectives/Outcomes

• Understand the definition(s) and scope of bioinformatics.
• Learn how to use computer programming techniques to solve problems in biology.
• Learn how to develop computer programs to accomplish specific, common, tasks in bioinformatics.
• Learn about selected topics in bioinformatics.

Major Topics Covered:

• Review of the Python programming language
• Introduction to the Jupyter notebook
• Introduction to core bioinformatics
  • Bioinformatics databases
  • Pairwise sequence alignment
  • BLAST search and related
  • Multiple sequence alignment
  • Phylogeny and evolution
• Exploration of topics in bioinformatics selected from:
  • Protein structure prediction
  • Gene regulatory network analysis
  • Phylogenetic inference
  • Population genetics
  • Comparative genomics
  • Medical informatics
  • Drug discovery
  • Automated image analysis
  • Visualization of large datasets
  • Network and systems biology
  • Microbiome analysis

Required Text

• Bioinformatics and Functional Genomics, Jonathan Pevsner, 3rd Edition
• ISBN-13 978-1118581780
• ISBN-10 1118581784
• http://www.bioinfbook.org/

Required Software

Download the graphical installer for Continuum Analytics' Anaconda Python distribution for your platform from https://www.continuum.io/downloads. Get python version 3.5. This software is free of charge.

Instructional Methods/Strategies

Lecture and in-class activities will provide the intellectual theory and conceptual understanding of science underlying computational biology and bioinformatics. Participation in class discussion will be expected and will require reading, searching the web and studying assignments prior to class. Students will write one major paper. Multimedia presentations will enhance student learning.

Methods of Evaluation

Methods of evaluation will include weekly homework assignments, a midterm examination and a final project. These will contribute to grades as follows:

Work	Proportion
Homework	60%
Midterm	15%
Final Project	25%

Applicable University Policies

See here.