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BIOENG131

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BIOENG 131 - Introduction to Computational Molecular and Cell Biology

Bioengineering Undergraduate COE - College of Engineering

Subject

BIOENG

Course Number

131

Department

Bioengineering

Course Level

Undergraduate

Course Title

Introduction to Computational Molecular and Cell Biology

Course Description

Topics include computational approaches and techniques to gene structure and genome annotation, sequence alignment using dynamic programming, protein domain analysis, RNA folding and structure prediction, RNA sequence design for synthetic biology, genetic and biochemical pathways and networks, UNIX and scripting languages, basic probability and information theory. Various "case studies" in these areas are reviewed; web-based computational biology tools will be used by students and programming projects will be given. Computational biology research connections to biotechnology will be explored.

Minimum Units

4

Maximum Units

4

Grading Basis

Default Letter Grade; P/NP Option

Method of Assessment

Written Exam

Instructors

Holmes

Prerequisites

BIO ENG 11 or BIOLOGY 1A (may be taken concurrently); plus a programming course (ENGIN 7 or COMPSCI 61A).

Repeat Rules

Course is not repeatable for credit.

Credit Restriction Courses. Students will receive no credit for this course if following the course(s) have already been completed.

-

Credit Replacement Courses

-

Course Objectives

To introduce the biological databases and file formats commonly used in computational biology. (2) To familiarize students with the use of Unix scripting languages in bioinformatics workflows. (3) To introduce common algorithms for sequence alignment, RNA structure prediction, phylogeny and clustering, along with fundamentals of probability, information theory and algorithmic complexity analysis.

Student Learning Outcomes

Students will be able to use knowledge from the lectures and lab sessions to write simple programs to parse bioinformatics file formats and execute basic algorithms, to analyze algorithmic complexity, to navigate and (for simple cases) set up biological databases containing biological data (including sequences, genome annotations and protein structures), and to use basic statistics to interpret results of compbio analyses.

Formats

Lecture, Laboratory

Term

Fall and Spring

Weeks

15 weeks

Weeks

15

Lecture Hours

3

Lecture Hours Min

3

Lecture Hours Max

3

Laboratory Hours

1.5

Laboratory Hours Min

1.5

Laboratory Hours Max

1.5

Outside Work Hours

8

Outside Work Hours Min

8

Outside Work Hours Max

8