Course code
Name of lecturer
Ferdinando Cicalese
Ferdinando Cicalese
Number of ECTS credits allocated
Academic sector
Language of instruction
I semestre dal Oct 1, 2018 al Jan 31, 2019.

To show the organization of the course that includes this module, follow this link * Course organization

Lesson timetable

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Learning outcomes

The course aims at providing the fundamental (methodological) tools for the design and analysis of algorithms with some emphasis on problems of interests for bioinformatics. In the presentation of the main technique of algorithm design, applications and example will be preferably taken from the area of bioinformatics and computational biology.

The course will provide the students with the knowledge and skills necessary to be able to model simple problems in terms of computational problems; to quantify the computational resources necessary to execute an algorithm, hence to compare different algorithmic solutions in terms of their computational cost. In particular, a student who profitably attended the course, will be able to evaluate the applicability and effectiveness of basic algorithmic design techniques to simple computational problems.


Basic definitions: Computational Problems and Algorithms
Analysis of algorithms: worst case and average case analysis;
Algorithmic complexity: asymptotic notations; basic tools for the analysis of algorithms; solution of recurrences;
Algorithms for searching sorting and selection.
Data Structure for the implementing a dictionary: queues, heaps, binary search trees, hash tables;
Design techniques: divide and conquer; greedy; dynamic programming;
Graphs and Graph algorithms: graph traversals, basic connectivity problems, topological sorting

Reference books
Author Title Publisher Year ISBN Note
J. Kleinberg, É. Tardos Algorithm Design (Edizione 1) Addison Wesley 2006 978-0321295354
Neil C. Jones, Pavel A. Pevzner An introduction to bioinformatics algorithms (Edizione 1) MIT Press 2004 0-262-10106-8
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein Introduction to Algorithms (Edizione 3) MIT Press 2009 978-0-262-53305-8

Assessment methods and criteria

The exam verifies that the students have acquired sufficient confidence and skill in the use of basic algorithmic design and algorithmic analysis tools.

The exam consists of a written test with open questions. The test includes some mandatory exercises and a set of exercises among which the student can choose what to work on. The mandatory exercises are meant to evaluate the student's knowledge of classical algorithms and analysis tools as seen during the course. "Free-choice" exercises test the ability of students to model "new" toy problems and design and analyse algorithmic solutions for it.

The exam can also be passed via two midterm tests (structured as the main final exam). The relative weight of the midterm tests is proportional to the part of the course on which their are based. The overall result of the midterm exams is only valid towards the registration at the one of the exams in February session.

The grade in "Algorithms" is given by the average of the grades achieved for the module "Algorithms for Bioinformatics" and the grade achieved for the module "Programming Laboratory II".