Home Page of I532:

I532
Fall 2004

Lecture: 2:30pm-4:20pm M JH248

Lab: 9:30am-10:45am W I109

Instructor: Sun Kim

Office

227 Informatics building
901 10th street

Office Hours (Tentative)

4:30 - 5:30 pm (Monday) 248 Jordan Hall
1:30 - 2:30 pm (Thursday) 227 Informatics
or by appointment

Course Outline

The goal of L529 is to teach issues in the design and implementation of bioinformatics tools and systems. The student will pursue a term project that either explores a new computational tool or develops an information system for large scale biological data mining.
The course will be divided into four parts:

study of probabilistic and algorithmic techniques in biological sequence analysis,

study of issues in the design and implementation of information systems for biological research,

literature survey on recent development in bioinformatics, and

a term project

Text Books

(REQUIRED)

Biological Sequence Analysis
Durbin, Eddy, Drogh and Mitchinson
0-521-62971-3, Cambridge University Press

(OPTIONAL)

Mastering Algorithm with Perl
Orwant, Hietaniemi, and MacDonald
0-56592-398-7, Oreilly

LEDA : A Platform for Combinatorial and Geometric Computing
by Kurt Mehlhorn (Author), Stefan Näher (Author)

The Boost Graph Library User Guide and Reference Manual
by Lie-Quan Lee, Andrew Lumsdaine, Jeremy G. Siek

Machine Learning
Thomas M. Mitchell
ISBN: 0070428077 1997 McGraw-Hill Companies,

Data Mining; Practical Machine Learning Tools and Techniques with Java Implementations
Ian H. Witten, Eibe Frank
ISBN: 1558605525 1999 Elsevier Science & Technology

Prerequisites

Bioinformatics
Knowledge equivalent to L519. here

Computer Science
Knowledge equivalent to C343/A594 (Data Structures) see here

Biology
Some understanding of biology. Try terminologies such as translation, transcription, promotors, exon, intron, splicing, SNP, gene expression profile, transcription factors, hybridization, codon, centromete, TATA box, alhpa-helix, beta-sheet, etc

Statistics/Probability
Undergraduate knowledge of Statistics/Probability

Grading

Exam, Quiz (30%): A programming assignment as an exam be sometime October.

Homework (20%):

Presentation of papers (10%): We will collect a set of recent papers on bioinformaitcs. We will discuss about what topics should be covered by a collection of papers by the end of October. Once we finalize the paper collection, starting from early November, a team of two students will present papers of your selection, focusing on the technical aspect of the paper. You may choose papers closely related to your term or thesis projects if all agree.

Term project (40%): The topic for your term project needs to be selected by the end of October. There will be two presentations and/or written reports, one in the middle of the semester and another at the end of the semester. The first should include the motivation and overview of the project. The second should describe the design and implementation of your project and provide some result with biological interpretation.

Lecture Schedule

We will cover the main textbook, Biological Sequence Analysis, as much as possible.

Topics not included in the text will be discussed a collection of papers. Everyone should read all research papers, including the papers you are not presenting.