BCB/GDCB/STAT/COM S 568 Brendel Spring 2008

Bioinformatics II. Advanced Genome Informatics.

BCB/GDCB/STAT/COM S 568 Brendel Spring 2008

Time & Location:    Tu, Th 9:30A - 10:50A (Units: 3); 1424 MBB
Instructors:    Volker Brendel (2112 MBB; Tel.: 294-9884)    Michael Sparks (2128 MBB; Tel.: 294-4063)
Teaching Philosophy:     emphasizes integration of research and textbook learning and interdisciplinary study.
Email:    VB, vbrendel@iastate.edu; MS, mespar1@iastate.edu
WWW:     http://gremlin1.gdcb.iastate.edu/~volker/
Office Hours:    by appointment
Grades:    will be determined as described below.
Schedule:     http://gremlin1.gdcb.iastate.edu/~volker/teaching/bcb568schedule.html
Computing Resources:     You may need access to UNIX or LINUX based computers for your project assignments.

Synopsis

Precipitated by an enormous increase in molecular sequence data (both DNA and protein), computational tools have become essential to molecular biology and genome research. Expertise in computational biology/bioinformatics is in great demand, and some level of proficiency in the subject is expected of anyone engaged in biological research at the molecular level. This course seeks to provide a general introduction to the subject as well as a discussion of several current research topics, with emphasis on statistical concepts and approaches. In this respect, this course is complementary to other courses offered at ISU that emphasize algorithmic issues and solutions (BCB 567, BCB 549). Lectures will cover the biological motivation of various problems and the theoretical foundations of modeling solutions. Homework assignments will include excercises and programming tasks for practical applications. Topics will include: statistical sequence models, Markov models, Hidden Markov models, score-based sequence analysis, amino acid substitution scoring matrices, gene structure prediction. The goal of the class is to prepare students to critically read and contribute to the relevant research literature.

Prerequisites

This interdisciplinary course is primarily directed at graduate and advanced undergraduate students in biology, computer science, statistics, or related disciplines who aspire to a professional career in this field. Familiarity with basic concepts and knowledge in molecular biology and statistics as well as programming experience (Perl, C, or C++) are assumed. Prerequisite courses are BCB 567, BBMB 301, Biol 315, Stat 430, and credit or enrollment in Gen 411. Good sources for fundamental probability and statistics concepts are

Taylor, H.M. & Karlin, S. (1998) An Introduction to Stochastic Modeling. 3rd edition. Academic Press, San Diego, USA.

and

Feller, W. (1971) An Introduction to Probability Theory and its Applications. Vol. 1, 2nd edition. John Wiley & Sons, New York.

A suitable text for the genetics and molecular biology background is

Atherly, A.G., Girton, J.R. & McDonald, J.F. (1999) The Science of Genetics. Saunders College Publishing, Fort Worth, USA.

Textbooks

There are now a growing number of good textbooks on bioinformatics and computational biology. We will not follow any particular text. However, some of the material in the course is covered in the textbooks, typically with different emphasis and exposition. Students are expected to take notes during lectures and to study the material independently outside of the classroom using textbooks of their choice or original sources. Some texts are available in the BCB office, MBB 2014, for perusal and short-term borrowing.

Selected Journals

Students will be expected to read current research literature in the field. The following list provides a selected relevant journals that are electronically accessible from ISU accounts. For more choices, see e-Journals @ ISU.

Assignments

Homework assignments will be posted regularly to deepen understanding of the lecture material (~3 assignments total). Written answers will be due two weeks after the assignment is posted (unless specified otherwise).

Expectations for the final project are perhaps best summarized in this dialogue.

Grading

In addition to the graded homework, there will be a written midterm examination, and students will also be called upon to discuss current literature and submit a final project. Approximate weights for the class grade: homeworks 1 and 2, 15% each; midterm examination, 20% (maximum of midterm I and midterm II scores); homeworks 4 and 5, 15% each; final project, 20% (note: as an alternative to the final project, submit solutions to homework problem set 3).