Biomedical Informatics 214 (also listed as Computer Science 274 and Genetics 214) Representations and Algorithms for Computational Molecular Biology  Spring 2007

Lectures: Tuesdays and Thursdays 2:45pm-4pm in Thornton 102
Sections: Fridays 10:00am-10:50am in Skilling 193 (Live on E5). Sections will not be held every week. Watch the schedule below and the class emails for information on sections dates and topics.
Internet: BMI 214 Course by streamed Internet video online on Stanford Center for Professional Development

Table of Contents

May 4:

Midterm: Monday, May 7 7:30-9pm in Thornton 102.

May 1:

REMINDER: Prof. Altman will be lecturing Friday 5/4 and 5/11 at 10-10:50am, in Skilling 193. Peggy Yao will give a section on Friday 5/18.

April 26:

There will be NO CLASS TODAY, Thursday April 26.

April 6:

We have posted notes which can assist you in learning the Python scripting language here. We strongly recommend that you take this opportunity to learn Python, which is a very useful, elegant scripting language. Especially when parsing text files, this is often much faster to code in than Java or C++. It may also be more convenient than Matlab which works well with numbers but is slightly less convenient when dealing with text. However, the choice of language for all projects is up to you. Next Friday we will have a section to go over these Python notes and any additional questions you may have.

April 5:

We would like to encourage anyone who does not feel that they have a strong biology background to attend the 10 AM session tomorrow (Friday, April 6th) in Skilling 193, Live on Stanford channel E5.

Based on feedback from previous years, you will get the most out of this session if you come ready to ask questions during the session itself. To give you a general idea of what will be presented (actual presentation may differ slightly) we have posted a PDF version online here.

Printed versions of the presentation will be available at the session (save trees and don't print your own if you are coming).

April 5:

Here is the dynamic programming grid corresponding to Professor Altman's example in class today of aligning AATGC with AGGC, with full pointers and the optimal aligment tracebacks in red. The 3 optimal-scoring alignments were:

AATGC
-AGGC

AATGC
A-GGC

AATGC
AG_GC

April 5:

As described in class, for a global alignment which penalizes end gaps, fill the matrix as described by Dr. Altman, and traceback the alignment from the position at the bottom right-hand corner (last row and last column). For a global alignment with cost free end gaps, each element in the first row and column is assigned the value zero, and then the scores are computed as in the global alignment, but the traceback is done from the highest score found in the last row or column, backwards to the first row or column.

April 4:

To all students who did not register the class via AXESS:
Please send the following information to biomedin214-spr0607-staff@lists.stanford.edu so that we can add you into the class mailing list.
Full name
SUNet ID
Preferred email to contact you

Instructor:

Russ B. Altman
Professor of Bioengineering, Genetics, & Medicine (and Computer Science by courtesy)
russ.altman at stanford.edu

Tiffany Murray (tiffany.murray at stanford.edu)
Department of Genetics
Lane L301, MC: 5120
650-725-0659

Yael Garten (ygarten at stanford.edu)
Office Hours: Tuesday, 1:30-2:30pm, BMI student lounge, MSOB X-215 (directions)

Peggy Yao (peggyyao at stanford.edu)
Office Hours: Thursday, 1:30-2:30pm, BMI student lounge, MSOB X-215 (directions)

Sam Pearlman (sampearl at stanford.edu)
Office Hours: Friday, 1-2pm, BMI student lounge, MSOB X-215 (directions)

Mailing Lists

• staff: biomedin214-spr0607-staff@lists.stanford.edu
  (This is the best way to reach us.)
• students: biomedin214-spr0607-students@lists.stanford.edu
  This list is automatically populated nightly with the list of students currently registered on Axess. You will be automatically added to the list after you have registered on Axess. It will be used by staff to send course-related announcements.

Newsgroup
To subscribe to the class newsgroup, su.class.biomedin214, log on to the news server nntp.stanford.edu. This is a great way to communicate with your peers, set up study groups, etc.
We suggest that you use this to discuss projects and assignments with one another as often, that will be your fastest way of receiving a response, especially when deadlines are coming up.

FAQ: (top)

Please read the Frequently Asked Questions prior to sending questions to the course staff.

Description: (top)

This course will introduce the basic computational issues and methods used in molecular biology, combining core lectures, programming assignments, with midterm and final. The course will introduce and use biological data sources available on the World Wide Web. Topics will include basic algorithms for alignment of biological sequences and structures, as well as more advanced representational and algorithmic issues in structure and sequence computation. These include, for example, dynamic programming algorithms for alignment, structural superposition algorithms, computing with distance information, 3D motif definition and computation, hidden Markov models, phylogenetic trees, statistical feature detection, genetic algorithms, design of data resources, automated analysis of biological literature, database integration, and collaborative environments for supporting biology.

• This course is normally taken for 4 units.
• It can be taken for 3 units by arrangement with instructor.
• A lecture-only, no assignment participation may be taken for 1 unit by arrangement with instructor. Students must attend all lectures, absences must be approved by the instructor. Enroll in BMI 216.

The course will be graded by performance on short homeworks (approximately 30%), long projects (approximately 50%), midterm and final (approximately 20%).

Midterm: Monday, May 7 7:30-9pm in Thornton 102.

Final: Friday, June 8 3:30-6:30pm in McCullough 115.

Each student is granted 7 "free" late days that can be used as extensions for any project or assignment. (Note that this is a total of 7 days for the entire quarter, not per assignment). Late days will be measured in 24-hour/day calendar days with no distinction for weekends or holidays, and will be rounded UP to the nearest integer (thus, 10 minutes late = 23 hours late = 1 day late). After you use up all your free days, your grade on late projects/assignments/exams will be reduced 10% for each late day. Extensions beyond the 7 free days may be granted at the discretion of the instructor (not the TAs) and must be requested prior to the due date.

For assignments:
Students may discuss and work on problems in groups but must write up their own solutions. When writing up the solutions, students must write the names of people with whom they discussed the assignment.

For programming projects:
Students may discuss ideas with others. However, programs are to be completed independently and should be original work. Code may not be shared. Names of students with whom programming ideas were discussed should be included with assignment.

Auditors for the course should take it for one unit as BMI 216. This course requires attendance at lectures, sign-in at each lecture (approval for missing a lecture), but does not require completion of homeworks or tests. It is for one unit, received for attending all lectures.

Auditors who want to sit-in on the course but not be officially signed up for 1 unit of credit should get approval from Dr. Altman, and will also be asked to attend all lectures, sign-in, and not do the homeworks or tests.

1. Programming skills are required at the level of CS106A/CS106B or CS106X. This course has a significant component of programming, and so students should enter it with ability to create moderately complex data structures, and implement algorithms using these data structures. Acceptable languages are outlined in the code policy.
2. Biology 40 or equivalent is recommended, since we will quickly move through many biology topics. It may be useful to have a textbook of molecular biology for reference during the course, for those who do not think about biology very much. We will have TA sessions devoted to biology brush-up.

You will need to have access to email (be sure you're registered on Axess so that you get email announcements sent to the course list), the course website, and the Stanford elaine machines. All of these resources are available to Stanford students at Sweet Hall and elsewhere as well as through remote (ssh) access. To log in, you will need to use your SUNet ID. If you don't have a SUNet ID, see http://sunetid.stanford.edu ASAP.

To log in to the "elaine" cluster machines, use a secure shell (ssh).

Windows: You will have to download a terminal emulation that allows ssh. Stanford offers a few free ones here; a popular ne is PuTTY. Directions for using Putty to connect to elaine:

Under "Host Name", enter elaine.stanford.edu
Under "Protocol", choose SSH
Press the "open" button.
A terminal window should appear, connected to elaine. Putty will tell you if there was an error.

OSX/*nix:

Open a terminal window
Type "ssh sunetid@elaine.stanford.edu"

(See http://www.stanford.edu/services/cluster/ and http://www.stanford.edu/services/cluster/which.html for more information on various campus machines.) Most course material will be placed on the course website in *.pdf (Adobe Acrobat) format, which allows the documents to be read on multiple platforms. Readers are available for free for Windows, Macintosh and many Unix platforms at the Adobe website.

Familiarize yourself with the Code/Language Policy before choosing a language and starting the first programming assignment.

Mount, D.W., Bioinformatics : sequence and genome analysis. 2nd edition (July, 2004), Cold Spring Harbor Laboratory Press. ISBN: 0879696877.

Optional readings will be suggested from this textbook throughout the course, and it covers approximately 70% of the material in the course. Available at the Stanford Bookstore. Copies on reserve at the Lane Medical Library and Math/CS library.

Other Recommended books that are more focused:

Kohane, I.S., Kho, A., Butte, A.J., Microarrays for an Integrative Genomics (Computational Molecular Biology). 2002, MIT Press. ISBN: 026211271X.

Durbin, R., Eddy, S.R., Krogh, A., Mitchison, G., Biological Sequence Analysis : Probabilistic Models of Proteins and Nucleic Acids. 1999, Cambridge Univ Pr. ISBN: 0521629713

Bourne, P.E., Weissig, H. (editors), Structural Bioinformatics. 2004, John Wiley & Sons. ISBN: 0471201995. This book is also available from the Wiley Interscience website at http://www3.interscience.wiley.com/cgi-bin/homepage/?isbn=0471721204 via the campus network.

Note on courses in computational biology: (top)

BMI 214 (also listed as CS 274) is this course. It has been taught since 1996 and is an introduction to representations and algorithms for analysis of sequence, structure and function. It requires programming skills and aims to give an understanding of the biological problems that arise, and how algorithms are developed to address them. It does not train students to be expert users of tools, but gives them an in-depth knowledge of some tools and a broad introduction to the technical issues in analysis of biological data. It is taught live on Tuesdays/Thursdays and is also on Stanford Online. Section is taught on Friday mornings.

Biochem 218 (also listed as BMI 231) is Doug Brutlag's course introducing computational molecular biology, also a number of years old. It is more geared towards gaining an expert understanding of existing tools and databases, and as such complements BMI 214 very nicely. There is no programming required. Most students take both eventually and learn a lot--even the areas where there is overlap are presented differently enough to round out one's understanding. For logistical reasons this course is also being taught on Tuesday/Thursday, and is on Stanford Online.

CS 262 (Computational Genomics) is Serafim Batzoglou's course. It focuses principally on algorithms for sequence assembly, analysis and comparison. It will have a strong CS algorithms and data structures component, probably with an element of software engineering as well. It is likely to complement both courses, although in the future, about 1/3 of BMI 214 may overlap sufficiently to require coordination--the part about sequence and string analysis. The coordination has not been done as of now, however. It does not contain much on 3D structure computation and functional computing, judging from the syllabus. The course will be taught live. You should ask Prof. Batzoglou about his plans to offer it via Stanford Online.