Bioinformatics:info:2007

From Shiu Lab

Contents 1 When/Where 2 Description 3 Objectives 4 Requirements 5 Text books 6 Grading & other general policies 6.1 About your grades 6.2 Attendance Policy 6.3 Academic Integrity (mind you, I didn't come up with this...) 7 Syllabus

When/Where

Offerred	Spring, 2007
Class hours/location	TR – 1-2:20pm, Plant Biology 151 (east end of building).
Instructor	Shin-Han Shiu
Office	S-306 Plant Biology Bldg. (south end of building)
Email	shius at msu dot edu (I’ll respond in 24 hours)
Office phone	353-7196 (prefer email)
Office hours	TR 2:20-4pm or by appointment. To make an appointment, you can either stop by my office or email.

Description

The availability of genome sequences and large-scale functional characterization datasets has drastically transformed the biomedical research enterprise. With the ability to examine the whole genome and tens of thousands of genes at the same time, the major challenge is how to extract information from these enormous amounts of data. Bioinformatics, the science and techniques for organizing and analyzing biological data, allows us to meet the challenges of the genomics era. This course will provide an introduction for the datasets available, current tools for analysis, the quantitative concepts behind these tools, and hands-on experiences on how to develop simple bioinformatic tools for biological data analysis.

Objectives

The goals of this course are:

• Introduce the quantitative concepts that utilized in bioinformatic tools such as programs for sequence alignments, motif search, phylogenetic reconstruction, and others.
• Enhance understanding of the bioinformatic algorithms with weekly exercises that emphasize self-directed learning, critical thinking, and writing skills.
• Develop bioinformatic tools in interactive lecture sessions with inquiry-based research problems.
• Have students working on group projects that require team work, enhance their problem solving skills, and relate what you learn to real-world applications.

Requirements

• A introductory statistics course (such as STT200, 201, 231, 315, or 421).
• Biology courses covering organisms, ecology, evolution, genetics, molecular and cell biology (e.g. BioSci 110/111 sequence).
• Or permission from the instructor.

Text books

Assigned readings will be drawn from:

• Bioinformatics and Functional Genomics, Jonathan Pevsner 2003 - The book is expensive. I'd encourage you to get used ones from places like:
  • BestBookBuys
  • Amazon
• Guido van Rossum. 2006. Python tutorial. Python software foundation (free)

Grading & other general policies

About your grades

Exams (300pt)

They will consist of multiple choice and questions requiring essay-type answers. The material of each exam will cover lectures and readings of the preceding one-third of the course with a total of 300 points.

Exercises (100pt)

8 exercises will be given, 12.5 points each. They are to be solved by each student individually or as a group. In the later case, names of collaborators need to be included. Plagiarism is usually very easy to spot so please do not attempt. One point will be deducted from past due exercise and addition one point will be deducted every 12 hours.

Final project (125pt)

A project with 2-4 members will be carried out with 100 points. The project topics can be subjects related to your research projects or interests. The project is graded based on the following -

1. Project justification (20 points): a one-page document with background, significance of the project, and the planned approaches, and the expected outcome.
2. Progress report (20 points): a two-page document with 1/2 page on the background of the project and the rest with some details on the approach and the finding so far. Also need to provide information how the labor will be divided among team members.
3. Final report (45 points): a 5-8 page document written in the scientific paper format (strictly enforced) with introduction, methods, results, discussion, figures, figure legends, and references. Also need to include information how the labor are divided among team members.
4. Final presentation (40 points): a presentation with introduction, methods, results, implications, and future directions.

• The total is 525points, which translated to 105%, not a mistake. The extra 5% serves as extra credits.

Attendance Policy

• You are required by University regulation to attend every lecture.
• You are expected to take examinations as scheduled.
• Make-up examinations will only be given upon receipt of a medical excuse signed by a physician or approval of the instructor. If you cannot take an examination when scheduled, contact the instructor by e-mail or telephone when possible.

Academic Integrity (mind you, I didn't come up with this...)

• The principles of truth and honesty are fundamental to the educational process and the academic integrity of the University; therefore, no student shall:
  1. claim or submit the academic work of another as one's own.
  2. procure, provide, accept or use any materials containing questions or answers to any examination or assignment without proper authorization.
  3. complete or attempt to complete any assignment or examination for another individual without proper authorization.
  4. allow any examination or assignment to be completed for oneself, in part or in total, by another without proper authorization.
  5. alter, tamper with, appropriate, destroy or otherwise interfere with the research, resources, or other academic work of another person.
  6. fabricate or falsify data or results.

Syllabus

Date		Topic	Readings and other activities
1/9	T	What is bioinformatics, data types, and access	BFG chapter 1,2
1/11	R	Programming I: Unix basics and programming environments	Guest lecture: Sarah Payok (ACNS). PT chapter 2, exercise 1
1/16	T	Pairwise sequence alignment	BFG chapter 3
1/18	R	Programming II: Data types and control flow	PT chapter 3,4, exercise 2
1/23	T	Database search	BFG chapter 4
1/25	R	Programming III: Data structure, modules, and IO	PT chapter 5,6,7 exercise 3
1/30	T	Genome sequencing and assembly
2/1	R	Programming IV: Error handling, Biopython, database programming	PT chapter 8, exercise 4
2/6	T	Gene prediction, annotation
2/8	R	Mid-term I
2/13	T	Gene expression and its regulation I	BFG chapter 6, selected papers
2/15	R	Gene expression and its regulation II	Selected papers, exercise 5
2/20	T	Gene expression and its regulation III	BFG chapter 6
2/22	R	Microarray and array data analysis	BFG chapter 7, expercise 6
2/27	T	The R project and bioconductor	Exercise 5
3/1	R	Proteins, proteomics, and data analysis	BFG chapter 8, exercise 7
3/5-3/9		Spring break
3/13	T	Protein structure and pattern finding	BFG chapter 9, Project team selection
3/15	R	Protein and genetic interaction networks	Selected papers
3/20	T	Mid-term II
3/22	R	Metabolomics	Guest lecture: Yair Shachar-Hill (PLB). Project topic selection start
3/27	T	Metabolic network analysis	Guest lecture: Yair Shachar-Hill (PLB)
3/29	R	Metabolic flux analysis	Guest lecture: Yair Shachar-Hill (PLB). Project topic finalized, exercise 8
4/3	T	Multiple sequence alignments	BFG chapter 10
4/5	R	Sequence evolution and phylogeny	BFG chapter 11
4/10	T	Genome evolution	BFG chapter 11
4/12	R	Machine learning	Guest lecture: Rong Jin (CSE). Selected papers, Project progress report due
4/17	T	Data mining	Guest lecture: Pan-Ning Tan (CSE).Selected papers
4/19	R	Bioinformatics and systems biology	Selected papers
4/24	T	Student presentation on project outcomes	ISMB meeting abstracts for discussion on 4/26
4/26	R	Discussion the current and future impacts of genomics, bioinformatics, and systems biology	Project report due
4/30-5/4		Final exam