Courses:

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There has been an explosion of biological data in the past few years, such as the complete genome of many organisms from bacteria to human, the structures of some RNA and numerous proteins, and the expression profiles of thousands of genes by chip technology. Converting this enormous data to useful biological knowledge requires a multitude of computational and statistical tools, as well as novel conceptual perspectives. Progress in this task requires knowledge of a number of issues such as optimization, partitioning, pattern recognition, collective behavior, which are in the domain of statistical physics. Since the central task of statistical physics is to describe how complex behavior emerges from interaction of large numbers of basic elements, its tools and concepts should be valuable in bioinformatics. The aim of this course is to introduce and explore some topics at the interface of physics and biology.

Statistical Mechanics (8.333).

The presentation of material does not follow a specific textbook for this course. The following books are recommended references.

Alberts, Bruce, et al. Molecular Biology of the Cell. 3rd ed. New York, NY: Garland Pub., 1994. ISBN: 9780815316190 (hardcover), 9780815316206 (paperback).
It is a standard reference to modern biology.

Durbin, Richard, et al. Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge, UK: Cambridge University Press, 1998. ISBN: 9780521620413 (hardcover), 9780521629713 (paperback).
It describes some of the standard computational methods used in bioinformatics.

Frank-Kamenetskii, Maxim D. Unraveling DNA: The Most Important Molecule of Life. Translated by Lev Liapin. Reading, Mass: Addison-Wesley, 1997. ISBN: 9780201155846.
It presents several relevant topics in a way that should appeal to physical scientists.

Watson, James D., et al. Molecular Biology of the Gene. 5th ed. San Francisco, CA: Pearson/Benjamin Cummings, 2003. ISBN: 9780805346350, 0805346422.
It is another standard reference to modern biology.

Nelson, Philip. Biological Physics: Energy, Information, Life. New York, NY: W.H. Freeman, c2003. ISBN: 9780716743729.
It is a new textbook by a statistical physicist.

Howard, Jonathan. Mechanics of Motor Proteins and the Cytoskeleton. Sunderland, MA: Sinauer Associates, Publishers, 2001. ISBN: 9780878933341.

Finkelstein, Alexei V., and Oleg B. Ptitsyn. Protein Physics: A Course of Lectures. Boston, MA: Academic Press, 2002.

There are many excellent resources on the Web. Here are a few examples:

ITP Program on Bioinformatics

A Course by Prof. Goldenfeld on Statistical Physics of Biological Information and Complexity

A Course at Berkeley on Molecular Biophysics

Kimball's Online Biology Textbook

The homework assignments are an important part of this course, and the overall average homework score will count for 80% of the final grade. You may consult with classmates in "study groups," as long as you write out your own answers.

The complete schedule of assignments (there will be 8) with due dates is available in the calendar. Hyperlinks to the actual problem sets and solutions will be created as the term progresses. Problem sets are due by 5:00 pm on the due date. They can be turned in at lectures, or in to the appropriate homework cubby.

No problem sets will be accepted after the solutions have been provided. Late problem sets (before solutions are provided) may be accepted (with legitimate excuses) for a reduced grade as the discretion of the instructors.

A Final Project will count for 20% of the final grade, and should be planned in consultation with the lecturers by Ses #12.

Final grades will be determined from:

Your final letter grade will reflect our best attempt to evaluate objectively your performance in the course:

A: Exceptionally good performance, demonstrating a superior understanding of the subject matter, a foundation of extensive knowledge, and a skillful use of concepts and/or materials.

B: Good performance, demonstrating capacity to use the appropriate concepts, a good understanding of the subject matter, and an ability to handle the problems and materials encountered in the subject.

C: Adequate performance, demonstrating an adequate understanding of the subject matter, an ability to handle relatively simple problems, and adequate preparation for moving on to more advanced work in the field.

D: Minimally acceptable performance, demonstrating at least partial familiarity with the subject matter and some capacity to deal with relatively simple problems, but also demonstrating deficiencies serious enough to make it inadvisable to proceed further in the field without additional work.

F: Failed. This grade also signifies that the student must repeat the subject to receive credit.