85301 - Algorithms and Data Structures in Biology

Learning outcomes

By the end of the course, the student his familiar with the design and analysis of correct and efficient algorithms and data structures. In particular, the student has basic knowledge of algorithms and data structures. The student is able to design correct and efficient algorithms for common computational tasks in biology and to analyse existing algorithms and data structures.

Course contents

• Concepts of algorithm and computational complexity: definition of algorithm, recursive algorithms and iterative algorithms, asymptotic notation.
• Exhaustive Search: restriction mapping, motif finding.
• Greedy algorithms: sorting by reversals, approximate algorithms.
• Dynamic programming: edit distance, Manhattan distance.
• Divide and Conquer.

Readings/Bibliography

Neil C. Jones and Pavel A. Pevzner. An Introduction to Bioinformatics Algorithms. MIT Press, 2004.

Teaching methods

Class lectures; Practical exercises in the lab.

Assessment methods

The exam consists in a written test, and an optional oral examination. These activities aim at assessing that the student has acquired the necessary skills in designing efficient algorithms besides the theoretical foundations.

 

Students with learning disorders and\or temporary or permanent disabilities: please, contact the office responsible (https://site.unibo.it/studenti-con-disabilita-e-dsa/en/for-students) as soon as possible so that they can propose acceptable adjustments. The request for adaptation must be submitted in advance (15 days before the exam date) to the lecturer, who will assess the appropriateness of the adjustments, taking into account the teaching objectives.

Office hours

See the website of Enrico Malizia