Course Syllabus and Overview

CSC 385/685; PHY 327/627; BICM 715: Bioinformatics

Time:  10 am MWF

Instructors: Drs. David John and Jacquelyn Fetrow

Office: John: West 251; Fetrow: West 236 & Olin 301B

Email: djj@wfu.edu, fetrowjs@wfu.edu

Web page: http://www.wfu.edu/~fetrowjs/Teaching.htm

Office Hours: TBA

Course meeting time:  MWF 10 am; generally, Monday and Wednesday lectures are held in West 244.  Friday interactive laboratory sessions will be held in West 017.  West 017 is reserved for 2 hours on Fridays, so that you can continue to work in groups beyond the class time. 

Course requirements:

CSC 385/685: To get credit for this course number, students will be required to actively participate in the software engineering and algorithm design aspects of the course.  All students will be required to understand the research issues and master the key concepts in the field of bioinformatics. 

BICM 715; PHY 327/627: To get credit for this course number, students will be required to master the biotechnical details behind the projects and effectively communicate those details to the students who are doing the engineering and algorithm design.  All students will be required to understand the research issues and master the key concepts in the field of bioinformatics.

Course numbers and prerequisites:

CSC 385/685:  Prerequisite for registering for this course number is CSC 221 (or permission of the instructor).

BICM 715; PHY 327/627:  Prerequisites for registering for this course number are introductory courses in biology, chemistry, and molecular biology or biochemistry (or permission of the instructor).

Textbook:  Bioinformatics: Sequence and Genome Analysis, David Mount, 2nd edition

            It is not possible to cover all topics in this textbook during a single semester.  You will not be responsible for knowing those chapters that we do not cover in class, laboratory, or during the project. 

Reading assignments and quizzes:  Reading assignments (see schedule below) are to be done prior to class. Online reading quizzes, due before every MW lecture, cover the material in the reading assignments.  These will be due by 8 am the day of class.  There will be no reading quizzes prior to the Friday labs, though you should look over the reference material and the lab exercise before coming to lab.  The reading quizzes are to be completed without any assistance.

Research-based learning: The best way to learn to use bioinformatics and computational biology methods is to apply those methods in a research-based format. We will follow this learning approach in this course.  We will teach methods and theory, but you will apply the methods and theory to a problem for which we do not yet know the “right answer;” however, it is a problem in which we are interested.  The project topic will be presented in more detail in several weeks.  

 

 

 

 

 

Grading: 

            Reading quizzes (25 quizzes at 4 points each)                                 100 points

            Laboratory exercises (6 at 50 points each)                                        300 points (360 gr)

            Project parts (50 points each)                                                            300 points
              (scope v1, scope v2, design v1, design v2, documentation, user training session)

            Final project                                                                                        200 points

            Class participation, observations, and creativity                                50 points (100 gr)

            Final examination                                                                                100 points

            Total:                                                                                                   1050 points (1210 gr)

Graduate credit:  Students registered for any of the graduate course numbers and receiving graduate credit will be held to higher expectations than students receiving undergraduate credit. Graduate students will be expected to answer lab and exam questions in more detail.  Often, there will be an additional, more difficult question that graduate students must answer in addition to the other questions, so the total number of allowed points will be higher for graduate students.  Graduate students are expected to participate in class more often and to offer more insightful observations.

Software/hardware required: A laptop computer is required for this class.  You must bring the laptop computer to the Friday laboratories, as we will usually be connecting to the internet to learn to use bioinformatics tools.  Students registered for one of the CSC course number will be required to utilize certain programming tools and languages.

 

 

Tentative Schedule

Date

Topic

Reading Assignment (required prior to class)

Homework Assignment (due by 5 pm on listed date)

Lecturer

Wed Aug 25

Class overview; course numbers/ requirements; introduction to sequences and algorithms

Chapter 1 (Mount)

 

JF/DJ

Fri Aug 27

Laboratory 1:  gene and protein sequence databases; sequence formats

 

 

JF/DJ

Mon Aug 30

Protein and nucleic acid sequences

p. 40-59 (Mount)

 

JF

Wed Sep 1

Pairwise sequence alignment:  what it is; interpretation of output

Chapter 3 and p. 129-147 (Mount)

Laboratory 1 due

JF

Fri Sep 3

Laboratory 2:  Nucleic acid and protein sequence alignment programs on the internet

 

 

JF/DJ

Mon Sep 6

Alignment algorithms: dot matrix

Chapter 3 (Mount)

 

DJ

Wed Sep 8

Alignment algorithms: dot matrix

Chapter 3 (Mount)

Laboratory 2 exercise due

DJ

Fri Sep 10

Laboratory 3:  Alignment algorithms

 

 

DJ/JF

Mon Sep 13

Alignment algorithms: dynamic programming

Chapter 3 (Mount)

 

DJ

Wed Sep 15

Introduction to project: understanding the problem

 

Laboratory 3 exercise due

JF/DJ/ guest?

Fri Sep 17

Definition of project scope; work on scope document

 

 

JF/DJ

Mon Sep 20

Alignment algorithms: dynamic programming

Chapter 3 (Mount)

 

DJ

Wed Sep 22

Intro to protein structure

p. 410-434 (Mount)

Project Scope Document, version 1 due

JF

Fri Sep 24

Laboratory 4:  Protein secondary structure prediction

 

 

JF/DJ

Mon Sep 27

Protein structure prediction

p. 410-434 (Mount)

 

JF

Wed Sep 29

Protein structure prediction

p. 410-434 (Mount)

Laboratory 4 exercise due

JF

Fri Oct 1

Project scope and application design documents

 

 

DJ/JF

Mon Oct 4

Protein structure/function relationships; function prediction

p. 444-454 (Mount)

 

JF

Wed Oct 6

Secondary structure prediction algorithms: neural networks

p. 455-467 (Mount)

Final project scope document due

DJ

Fri Oct 8

Project design document

 

 

DJ/JF

Mon Oct 11

Secondary structure prediction algorithms: neural networks

p. 455-467 (Mount)

 

DJ

Wed Oct 13

Secondary structure prediction algorithms: neural networks

p. 455-467 (Mount)

Project design document, version 1 due

DJ; Midterm grades due Mar 13

Fri Oct 15

Fall Break!  No class

 

 

 

Mon Oct 18

Discussion of project and design documents

 

 

All

Wed Oct 20

Genome anatomy

p. 496-515 (Mount)

 

JF

Fri Oct 22

Project design document

 

 

JF/DJ

Mon Oct 25

Genomics and gene expression

Chapter 13 (Mount)

 

JF out of town

Wed Oct 27

Genomics and gene expression

Chapter 13 (Mount)

Final project design document due

JF

Fri Oct 29

Laboratory 5: gene expression and analysis

 

 

DJ/JF

Mon Nov 1

Analysis of gene expression experiment:: statistical and clustering

Chapter 13 (Mount)

 

DJ

Wed Nov 3

Analysis of gene expression experiments:  statistical and clustering

Chapter 13 (Mount)

Laboratory 5 exercise due

DJ out of town

Fri Nov 5

Project implementation (status update)

 

 

 

Mon Nov 8

Proteomics:  protein expression and modification

 

 

JF

Wed Nov 10

DNA sequencing:  how is it done?

p. 30-40 (Mount)

First working version of project due

JF

Fri Nov 12

Project testing and validation

 

 

 

Mon Nov 15

Genome sequencing and assembly

p. 30-40, 511 (Mount)

 

JF

Wed Nov 17

Gene prediction algorithms: HMMs

Chapter 9 (Mount)

 

DJ

Fri Nov 19

Laboratory 6:  gene prediction and HMMs

 

 

DJ/JF

Mon Nov 22

Gene prediction algorithms: HMMs

Chapter 9 (Mount)

 

DJ

Wed Nov 24

Thanksgiving break!  No class

 

 

 

Fri Nov 26

Thanksgiving break! No class

 

 

 

Mon Nov 29

User training session

 

Laboratory 6 due

 

Wed Dec 1

User training session

 

 

 

Fri Dec 3

Final project

 

Final project/ documentation due; take home final exam distributed

 

Tues Dec 7

Take home final examination due

 

Take home final examination due