Computer Science M - Z

Academic Year 2022/2023 - Teacher: GIULIA RUSSO

Expected Learning Outcomes

At the end of the course, the student will acquire information theory basic concepts and programming and reasoning systems global knowledge; He will know the basic concepts of algorithms and he will be able to identify the main principles. Finally, he will own a global vision of the computer science applications to life science and drug discovery process.

Course Structure

Through lessons and practical sessions at the end of each learning unit (when planned).

If the lessons are given in a mixed or remote way, the necessary changes with respect to what was previously stated may be introduced, in order to meet the program envisaged and reported in the syllabus.

To guarantee equal opportunities and in compliance with the laws in force, interested students can ask for a personal interview in order to plan compensatory and / or dispensatory eventualities, based on the didactic objectives and specific needs. It is also possible to contact the referent teacher CInAP (Center for Active and Participated Integration - Services for Disabilities and / or SLD) of our Department, Prof. Teresa Musumeci.

Required Prerequisites

Not requested.

Attendance of Lessons

Mandatory attendance according to the teaching regulation of the CdLM in Pharmacy as reported in the following link: http://www.dsf.unict.it/corsi/lm-13/regolamento-didattico.

Detailed Course Content

Section 1.

Information theory basic concepts; Hardware, Software; Information technology; Computers types; PC components; Computer performances. Hardware: CPU; Memory; I/O peripherals; Memory devices. Software: applications, operating systems; Graphical User Interface; System development.

Section 2.

Computer networks: LAN, WAN; Intranet, extranet; Internet; PSTN line; Net applications; Digital world: e-mail, e-commerce. WEB; Basic concepts of Computer Network Security.

Section 3.

Algorithms; Algorithms properties; Descriptions; Constants and Variables; Propositions and Predicates; Flowcharts; Composition Schemes; Iterative Algorithms; Arrays; Structural analysis; Recursive Algorithms; Complexity: basic concepts; Numeration systems; Positional; Conversions; Binary operations; 8 and 16 numeral systems; Complements; Information coding; Bits, bytes and words; BCD Coding; Control bits; Computer arithmetic;

Section 4.

Computer Science Applications to Life Sciences and Drug Discovery

Textbook Information

Teacher's notes.

Course Planning

 SubjectsText References
1Argomento 1https://www.combine-group.org/assets/attachment/slide/modulo_informatica_generale_sfa.pdf
2Argomento 2https://www.combine-group.org/assets/attachment/slide/modulo_reti.pdf
3Argomento 3https://www.combine-group.org/assets/attachment/slide/modulo_algoritmi.pdf

Learning Assessment

Learning Assessment Procedures

Trough oral and written evaluation test.

If needed, the evaluation test could be performed also remotely.