The attendance policy is that you are allowed one unexcused absence in the first week, two unexcused absences in the first four weeks, and four unexcused absences in the first eight weeks. On exceeding these limits, you may be dropped from class.

The UA policy concerning class attendance, participation, and administrative drops is available here. The UA policy regarding absences for any sincerely held religious belief, observance or practice will be accommodated where reasonable, and is available here. Absences preapproved by the UA Dean of Students (or dean’s designee) will be honored (see the policy here).

• Hans-Joachim Böckenhauer and Dirk Bongartz,
  Algorithmic Aspects of Bioinformatics,
  Springer-Verlag, Berlin, 2007.
  (Surveys combinatorial algorithms in computational biology.)
  
  
• Peter Clote and Rolf Backofen,
  Computational Molecular Biology: An Introduction,
  John Wiley and Sons, Chichester, England, 2000.
  (Broad coverage of recent material with an emphasis on probability and optimization.)
  
  
• Richard Durbin, Sean Eddy, Anders Krogh, and Graeme Mitchison,
  Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids,
  Cambridge University Press, New York, 1998.
  (Emphasizes hidden Markov models for sequence comparison.)
  
  
• Dan Gusfield,
  Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology,
  Cambridge University Press, New York, 1997.
  (Clear exposition of exact string matching.)
  
  
• Pavel Pevzner,
  Computational Molecular Biology: An Algorithmic Approach,
  MIT Press, Cambridge, Massachusetts, 2000.
  (In-depth treatment of genome rearrangements.)
  
  
• David Sankoff and Joseph Kruskal, editors,
  Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison,
  Addison-Wesley, Reading, Massachusetts, 1983.
  (A classic collection on sequence comparison and its applications.)
  
  
• João Setubal and João Meidanis,
  Introduction to Computational Molecular Biology,
  PWS Publishing, Boston, 1997.
  (A broad survey of computational biology for computer scientists.)
  
  
• Michael Waterman,
  Introduction to Computational Molecular Biology: Maps, Sequences and Genomes,
  Chapman and Hall, London, 1995.
  (In-depth treatment of the statistics of sequence comparison.)

• Homework 1 (partial solutions): due September 21.
  
• Homework 2 (partial solutions): due October 5.
  
• Homework 3 (solutions): due November 7.

• Midterm: October 12.
• Final: December 11, 3:30-5:30pm.

• Programming project: due November 30.
• Research project: due December 5.

Course grades use the regular scale of A, B, C, D, and E. Grades are determined from a weighted average of the percentage of points earned on homeworks, exams, and projects.

Attaining a weighted score of at least 90% guarantees an A in the course, at least 80% guarantees a B, at least 70% guarantees a C, and at least 60% guarantees a D. These thresholds may be lowered, but will not be raised.

The awarding of points on homework and exam questions is roughly according to the following scheme. Having the right solution idea and the right technical execution of this idea earns at least 90%. (Only a perfect write-up that cannot be improved earns 100%.) Having the right idea but with errors in its execution is at least 80%. Having the wrong idea and errors in its execution, but demonstrating comprehension of the material, is at least 70%. Having the wrong idea, errors in execution, and deficiencies in comprehension, is roughly 60%. Work that shows no understanding is roughly 50%.

On homework and exam questions, writing an answer that relates to the question guarantees at least 50% of the points for the question (which is a failing percentage). No points are awarded for writing nothing.

Homeworks may contain bonus problems. Points earned on bonus questions are not added to points for required questions. Bonus points are tallied separately at the end of the semester, and considered subjectively as a measure of effort when deciding whether to move up a student who is near a letter-grade boundary.

On homework, very-high-level ideas can be discussed with friends, but solutions must represent individual work and must be written up separately. Use of solutions from previous offerings of the course is not permitted. Any material from the Internet that is used in a solution must be cited by its URL; to not cite it is plagiarism, which is considered cheating. (For more information, see the Department of Computer Science Course Policy on Collaboration and the University Code of Academic Integrity.)

When turning in solutions to homeworks, write only on one side of the paper, start each problem on a separate page, put the problems in the correct order, and staple the pages together. Neatness, and especially conciseness, is required to earn the highest marks. If a problem eludes solution, state this up front and write down only what you know to be correct. Rambling at length about attempts that didn't succeed may result in more points being deducted.

Requests for regrading homeworks or exams must be submitted within one week of receiving the graded homework or exam.

Homework that is late (submitted after the due date and time) is not accepted.

Requests for an incomplete (I) or a withdrawal (W) must be made in accordance with university policies.

I   Biological sequence analysis

• String matching: Exact matching of sequences using suffix trees, suffix arrays, and the Burrows-Wheeler transform.
• Sequence aligment: Inexact matching of sequences, local and global alignment, sequence database searching, affine gap costs, convex gap costs, multiple sequence alignment, inverse parametric alignment, and genome alignment.

II   Higher-level analysis

• Sequence assembly: Reconstructing the DNA sequence of a genome from next-generation sequencing data; mapping sequencing reads to a reference genome.
• Evolutionary tree reconstruction: Reconstructing evolutionary trees by compatibility-, parsimony-, maximum likelihood-, and distance-based methods, using sequence or gene-order data.
• Genome rearrangement: Computing evolutionary distances between genomes in terms of inversion, translocation, and transposition events.

The Department of Computer Science is committed to providing and maintaining a supportive educational environment for all. We strive to be welcoming and inclusive, respect privacy and confidentiality, behave respectfully and courteously, and practice intellectual honesty. Disruptive behaviors (such as physical or emotional harassment, dismissive attitudes, and abuse of department resources) will not be tolerated. The complete Code of Conduct is available on our Department website. We expect you to adhere to this code, as well as the UA Student Code of Conduct, while you are a member of this course.

To foster a positive learning environment, students and instructors have a shared responsibility. We want a safe, welcoming, and inclusive environment where all of us feel comfortable with each other and where we can challenge ourselves to succeed. To that end, our focus is on the tasks at hand and not on extraneous activities (such as texting, chatting, reading a newspaper, making phone calls, web surfing, and so on).

Inclusive Excellence is a fundamental part of the University of Arizona’s strategic plan and culture. As part of this initiative, the institution embraces and practices diversity and inclusiveness. These values are expected, respected, and welcomed in this course.

Students are asked to refrain from disruptive conversations with people sitting around them during lecture. Students observed engaging in disruptive activity will be asked to cease this behavior. Those who continue to disrupt the class will be asked to leave lecture or discussion and may be reported to the Dean of Students.

Some learning styles are best served by using personal electronics, such as laptops and iPads. These devices can be distracting to other learners. Therefore, students who prefer to use electronic devices for note-taking during lecture should use one side of the classroom.

The UA Threatening Behavior by Students Policy prohibits threats of physical harm to any member of the University community, including to oneself.

It is already UA policy that class rosters are provided to instructors with a student’s preferred name. Students may share their preferred name and pronoun with members of the teaching staff and fellow students, as desired, and these gender identities and gender expressions will be honored in this course. As the course includes group work and in-class discussion, it is critical to create an educational environment of inclusion and mutual respect. In this class, to be inclusive of all gender identities and expressions, students will be referred to by their first or last names, the pronoun of their choice, or by default, the pronoun “they”.

Our goal in this classroom is that learning experiences be as accessible as possible. If you anticipate or experience physical or academic barriers based on disability, please let the instructor know immediately to discuss options. You are also welcome to contact the Disability Resource Center (520-621-3268) to establish reasonable accommodations.

If you have reasonable accommodations, please plan to meet with the instructor by appointment or during office hours to discuss accommodations and how course requirements and activities may impact your ability to fully participate.

Please be aware that the accessible table and chairs in this room should remain available for students who find that standard classroom seating is not usable.

Students are encouraged to share intellectual views and discuss freely the principles and applications of course materials. However, graded work and exercises must be the product of independent effort unless otherwise instructed. Students are expected to adhere to the UA Code of Academic Integrity as described in the UA General Catalog.

The University Libraries have excellent tips for avoiding plagiarism, available here.

Selling class notes or other course materials to other students or to a third party for resale is not permitted without the instructor’s express written consent. Violations to this and other course rules are subject to the Code of Academic Integrity and may result in course sanctions. Additionally, students who use D2L or UA e-mail to sell or buy these copyrighted materials are subject to Code of Conduct Violations for misuse of student e-mail addresses. This conduct may also constitute copyright infringement.

The University is committed to creating and maintaining an environment free of discrimination and harrassment (see the policy here). Our classroom is a place where everyone is encouraged to express well-formed opinions and their reasons for those opinions. We also want to create a tolerant and open environment where such opinions can be expressed without resorting to bullying or discrimination of others.

UA academic policies and procedures may be found here. Student assistance and advocacy information is available here. Campus health information may be found here. OASIS sexual assault and trauma services are available here.

Information on confidentiality of student records is here.

Information contained in the course syllabus, other than the grade and absence policy, may be subject to change with advance notice, as deemed appropriate by the instructor.

The grade distribution for the overall course score is posted above.