Syllabus for CSCE 496/896 (Fall 2002)

Up-to-date information is at http://www.cse.unl.edu/~sscott/CSCE496-CB

CONTENTS

• COURSE INFORMATION
• COURSE OBJECTIVES
• COURSE ELEMENTS
• MISCELLANY

COURSE INFORMATION

PREREQUISITES: CSCE 310 (Data Structures & Algorithms), STAT 380/880 (Prob. and Stats.)

TIME: 3:30-4:45 Monday, Wednesday

CLASSROOM: Ferguson 112

TEXTBOOKS:

Required: Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, by Richard Durbin, Sean Eddy, Anders Krogh, and Graeme Mitchison. Cambridge University Press, 1998. ISBN 0-521-62971-3.

Optional, but recommended: Computational Molecular Biology: An Introduction, by Peter Clote and Rolf Backofen. John Wiley & Sons, 2001. ISBN 0-471-87252-0.

Also useful: Introuction to Computational Molecular Biology, by Joćo Carlos Setubal and Joćo Meidanis PWS Publishing Company, 1997. ISBN 0-534-95262-3.

These three books are on reserve at love library.

COURSE OBJECTIVES

The biological problems we will study include sequence alignments, protein family modeling, and phylogeny. The approach we will focus on is hidden Markov models, though we will also discuss dynamic programming as well as machine learning models like decision trees and artificial neural networks. In this course we will follow the book closely, but may occasionally supplement it with other relevant work.

COURSE ELEMENTS

You may consult each other for assistance on the homework, but you must write up your results in your own words and indicate whom you consulted. You must use some document processing package (e.g. ) to write your homework submissions, and you must submit your reports electronically in pdf format (see ``Help on Creating pdf Files'' and ``Help with LaTeX, etc.''). You must also write as clearly and concisely as possible. Presentation of your results is as important as the results themselves, and will be heavily weighted in grading. If I cannot understand what you wrote due to poor writing, etc., then I cannot award full credit, even if your answers are correct. Thus I recommend that you ask someone to proofread your write-ups before you submit them, to check for clarity, typographical errors, etc. If English is not your native language, then I strongly recommend this!

Finally, ensure that all your files (e.g. program code, homework write-ups) are reasonably well-protected. You will be held partially responsible if someone copies your files and submits them to me as homework solutions.

EXAMS
There will be no exams in this course except for the prerequisite test, which will evaluate your understanding of this course's necessary background material as well as your writing ability.

TOPIC SUMMARIES
After we complete each topic in lecture, you will submit a brief (3-5 pages) summary of that topic. This is due one week (at 11:59:59 p.m.) after we finish covering that topic in class (as with the homeworks, all submissions must be electronic in pdf format). No collaboration is allowed! Your summary will be based on the lecture, relevant readings from the text, and any other supplementary material. Your summary should include at least the following: (a) an overview of the ``big picture'' of that topic; (b) a description of what you feel are the most and least interesting results related to that topic; (c) 2-3 questions on material that you did not understand from the readings and lectures; (d) 2-3 interesting research ideas related to this topic; and (e) a detailed description of one subtopic. This summary must be in your own words! If you merely copy material from the textbook or the papers, you will be severely downgraded. Finally, as with the homeworks and projects, quality of writing and brevity will be heavily weighted in the grading.

At the end of the semester, I will drop your two lowest topic summary grades when computing your final average score on the topic summaries. In addition, each of you will be expected to grade about 7-10 other students' submissions of one topic summary. For this particular topic summary, you will receive a perfect score so long as you grade according to the above guidelines. So if you grade students' submissions for e.g. the topic summary on pairwise alignment, then you need not submit your own summary on that topic.

PROJECT
In this course you will do a substantial project. This project can be: (1) a very extensive literature search and summary on a particular topic, (2) a good implementation and evaluation of a known result in computational biology, or (3) a small (but nontrivial) amount of original research related to machine learning. You may work on these projects individually or in groups. Later this semester I will set a deadline for submission of 1-3 paragraph proposals on your projects. You must do this in order to get full credit for your project, and you must get my approval on it before starting work on your project.

You will summarize your project results in a written report and an oral presentation. If your project involves an implementation, then you may be asked to also give a brief demonstration. The written report must use a professional writing style similar to that found in an ACM or IEEE journal, including abstract, introduction, summary of related work, your contribution, references, and an appendix (if necessary). The oral presentation will be to the entire class at the end of the semester: during dead week (December 9-13), and if necessary, during the week prior to dead week (December 2-6). You will submit your written report to me no later than December 13 (the last day of dead week). In accordance with UNL dead week policies, you have now been informed in writing of the nature and scope of this project prior to the eighth week of classes.

DUMB QUESTION ASKER
Before each lecture, I will select a student who will be required to ask three questions during that lecture. During your assigned lecture, you may ask any question concerning any course material that you do not understand. If you completely understand the material, then you may ask any question that you feel would help the other students (even if you already know the answer yourself). If you cannot think of a question to help the rest of the class, then any ``dumb question'' (e.g. ``Who will win the game on Saturday?'') will suffice. But you must ask three questions during your assigned lecture.

GRADING
The above items will be weighted as follows:

prereq test: 5%

hwks: 30%

proj. report: 25%

proj. pres.: 15%

topic summaries: 15%

subjective: 10%

Your subjective score will be based on your fulfillment of your duties as dumb question asker as well as my impression of your effort put forth to participate in class, participate out of class, and to learn the course material. Thus actively asking questions and making comments in class and seeing me outside of class will help your grade.

In computing your letter grade I will start with the following base scale:

90% = A

80-89% = B

70-79% = C

60-69% = D

59% = F

You will receive a ``+'' with your grade if the last digit of your score is a 7 or higher, and a ``-'' if the last digit is a 3 or lower. I will scale up from this base scale if necessary. So if you get an 87% in this course you are guaranteed a B+ (similarly, an 82% guarantees a B-), but your grade might be higher depending on your performance relative to the rest of the class. Note that students taking CSCE 896 require a B to pass the course; a B- is insufficient. Similarly, CSCE 496 students in the Arts & Sciences College require a C (not a C-) for this course to count towards their major.

In general, students registered for CSCE 896 will be graded more stringently on everything and will have more problems to solve on the homework.

Academic dishonesty of any kind will be dealt with in a manner consistent with the CS&E Department's Policy on Academic Integrity. You are expected to know and abide by this policy.

MISCELLANY

Last modified 16 August 2011; please report problems to sscott AT cse .