Algoritmi e Linguaggi per Bioinformatica: Algoritmi
(academic year 2012/2013)
|Title of course:|| Algoritmi e Linguaggi per Bioinformatica: Algoritmi (2nd term of 2012/2013)
zsuzsanna DOT liptak AT univr DOT it
(Please put "Corso Algoritmi di Bioinformatica" in the subject line.)
Times: ||Mon 11.30 - 13.30 and Wed 8.30 - 10.30
|Place:||Lecture hall H
|Tue 11.30 - 13.30
and by appointment
|Office:||Ca' Vignal, 2, 1st floor, right corridor, stanza 1.79
- Exam results of 3/6/2013 here.
Current information: schedule, materials.
- Project presentation program here.
- Here are some tips how to make a
good presentation (updated).
- The project descriptions can be found here.
(Are you looking for last year's course?)
Note to students: If you have not yet received an email from me but you are following this course (and want to get the credits) then please send me an email, so I can include you in the mailing list.
GOALS of the course: 1. to learn about some basic problems and algorithms behind common bioinformatics applications (alignment, sequence similarity, phylogenetics), and 2. to get an idea of some basic computational issues (complexity, efficiency, limitations).
CREDITS: The credits for this course are given together with the first part of this module (Linguaggi, 1st term 2011/2012). The total grade (voto) for the module "Algoritmi e Linguaggi per Bionformatica" will be 50%
Linguaggi and 50% Algoritmi.
The grade (voto) for this course (Algoritmi) is made up of a written part and an oral part.
The written part can either be taken as one written exam of 3 hours at the end of the course, or in two parts: one midterm (2 hours, covers the first half of the course, April), and one final exam (2 hours, covers the second half of the course, June).
The oral part consists of presenting a topic, preferably using digital slides; we will choose the topic together, according to the student's background and interests. The presentation can be done either alone or in two (10-15 mins per person, plus questions).
Alternatively, you can take an oral exam on the complete contents of the course. Note: The presentation can be done only once (if you repeat, you have to take the oral exam)!
LANGUAGE: Lectures are in English; however, questions can be asked in English or Italian. Written exams will be in Italian only, except if an English version is also requested; answers can be given in Italian or in English, main thing that they be legible. Presentation can be given in Italian or in English, your choice; if you choose to give it in English, then linguistic quality will not influence the grade, of course.
A note on ATTENDANCE: As in most university courses, attendance of classes is not mandatory. All of what I teach in this course is completely standard and is contained in any algorithmically oriented bioinformatics book (see list on this page). In the exam, you will be asked to do things like compute an alignment of two strings, given a score function. You can learn this from any book or online course. However, I strongly believe that one gains much more from attending a course than from only studying by oneself. University classes give the student the opportunity of following a live course given by a live lecturer. If nothing else, attending the course forces you to spend a certain amount of time each week studying for this course. No handouts or slide presentations can completely substitute a lecturer. So if you can in any way make it, I would advise you to attend. If you can't, you have to rely on the notes of your colleagues and/or on books.
(For the real one, please check here)
Part I: Sequence Analysis
- Pairwise sequence alignment
- Algorithm analysis
- Multiple sequence alignment
- String similarity and distance
- Scoring matrices
- Heuristics: FASTA, BLAST
- ---Midterm exam---
Part II: Phylogenetics
- algorithms for distance-based data
- character-based data, Perfect Phylogeny
- Small Parsimony: Fitch's algorithm
- Large Parsimony: heuristics
- Some basic statistics for bioinformatics
- ---Final exam---
BOOKS: There are many books on bioinformatics, and most, if not all, will contain what we cover in this course. The following is my own selection.
Two books which are more oriented towards applications are the following. Please note that their depth of coverage of the underlying algorithms is not always sufficient for this course; however, they are valuable for their emphasis on the biological viewpoint, and their presentation of the issues and applications in very user-oriented terms:
- João Setubal, João Meidanis: Introduction to Computational Molecular Biology (1997).
This is my main reference. There is one copy in the library: during the course, you can check it out for three days only. I personally really like this book. It concentrates on the algorithmic angle, gives concise background on the biological motivations, and treats sidelines only briefly. It is concise and good for teaching. It is unfortunately a bit dated, so some current topics are not treated (but everything we cover is).
- Neil C. Jones and Pavel A. Pevzner: An Introduction to Bioinformatics Algorithms (2004).
There are 4 copies in the library, which you can check out for 3 days. I don't use this book very much, but I will try to give the corresponding chapters for each lecture.
- R. Durbin, S. Eddy, A. Krogh, G. Mitchinson: Biological Sequence Analysis (1998).
This is a very nice algorithmic book, with an emphasis on probabilistic models.
- Dan Gusfield: Algorithms on Strings, Trees, and Sequences (1997).
This is the book on string algorithms. On top of being a very thourough book on string algorithms, it also explains at length applications, of each problem and algorithm, in complutational biology.
- Joseph Felsenstein: Inferring Phylogenies (2004).
This is the standard book on phylogenetics.
- Hans-Joachim Böckenhauer and Dirk Bongartz: Algorithmic Aspects of Bioinformatics (2010).
This is a very mathematical book, more for research than for teaching, interesting mainly for those with a mathematical/computer science background who want to continue in this field. Also includes recent research areas such as haplotyping and genome rearrangements.
- Cormen, Leiserson, Rivest (& Stein): Introduction to Algorithms (different editions, 1990-onwards). This is the "bible" on algorithms. Everyone interested in algorithms should have a copy of this book. Since there are so many editions around, one can easily find a cheap second hand copy.
I use the following two lecture notes from my former university Bielefeld a lot. Note that they are much more detailed than what we cover, and sometimes use different notation. They can be useful for certain topics, and I will assign some chapters for the oral presentations; when the class is exactly based on these lecture notes, then I will say so.
- David M. Mount: Bioinformatics: Sequence and Genome Analysis (2004).
- Arthur Lesk: Introduction to Bioinformatics (2008).