The course deals with new ways of approaching biological problems as well as understanding basic principles of biology through computer science, by: a) developing new algorithms in order to evaluate the relationships between big data sets; b) by analyzing and interpreting different types of data including nucleotide and amino acid sequences, protein structures and structural and functional domains, and c) developing tools that allow access and management of different types of information.

To familiarize students with the concepts, tools and applications of Bioinformatics in order to address biological questions/problems. Knowledge: At the end of the course students should be able to: a) search and manage the biological information stored in Biological Databases, b) Use computational tools and programming methods to draw conclusions and get answers to biological questions - Skills: At the end of the course students will be conversant with: a) the scientific field of Bioinformatics, b) the way biological data are organized, how to access them and how to submit new data, c) using bioinformatics tools, d) developing methods and computational tools for exporting information, e) a programming language (perl) for the management and interpretation of biological information - Abilities: At the end of the course students should be able to: a) Search in biological databases, b) Search and use bioinformatics tools, c) Write programs –algorithms in Perl language, d) Work independently or as a team.

Bioinformatics and Computational Biology (1 Hour)

Elements of Computer Science – Computer Applications in Biology (3 Hours)

Operating Systems (Unix / Windows) – Introduction to PERL (6 Hours)

Computer networks and their uses (email, telnet, ftp…) - Internet – World Wide Web (www) - Web browsers – Web pages - HTML / XML (2 Hours)

Protein and DNA Databases – Specialized Protein and DNA Databases – Annotation problems (2 Hours)

Protein and Genome Information Resources and Tools (2 Hours)

Genome Projects (1 Hour)

Next level of the genetic code - Protein folding - Protein-protein interactions - Metabolic pathways – Protein assembly and self-assembly (3 Hours)

Genome Analysis - Difficulties in experimental determination of protein structure and function - Structural Genomics , Microarray analysis(1 Hour)

Computational Analysis to bridge the ‘gap’:

1. Data Base Management Systems

2. Data Mining-Ontologies

Computational analysis of sequences:

Α. Similarity based Methods (alignment of pairs of sequences – similarity matrices – statistical parameters of alignment similarity – global and local alignment – heuristic methods of alignment (FASTA and ΒLAST algorithms) – multiple sequence alignment – phylogenetic trees) - Searching and finding motifs (3 Hours)

 Β. Empirical methods / A priori methods (2 Hours)

 C. Μachine Learning Techniques (Neural Networks, Ηidden Markov Models etc.) (2 Hours)

Analysis of DNA sequences (e.g ΟRFs prediction etc.) (1 Hour)

 Analysis of protein sequences and structures (1 Hour)

Algorithms for protein secondary structure prediction (1 Hour)

Finding periodicities in protein and DNA sequences (1 Hour)

Prediction of transmembrane segments and topology of membrane proteins (1 Hour)

Fold recognition methods (1 Hour)

Protein structure comparison and alignment (1 Hour)

Comparative homology modelling and threading (1 Hour)

Modelling of protein conformation utilizing molecular mechanics and dynamics (1 Hour)

Principles and methods of ligand docking to proteins – Drug design (1 Hour)

Protein – protein docking (1 Hour)

1. Introduction to Unix  (I) - 2. Protein and Nucleic acid Databases - Specialized Protein and Nucleic acid Databases - Analysis Tools of Nucleic acid and Protein Sequence and Structure Databases - 3. BLAST – FASTA -– CLUSTAL – Tools for similarity searches and multiple sequence alignments - 4-7. Perl Programming for Biologists - Bioinformatics Applications - 8. Analysis of protein-protein interactions, protein networks and biological pathways

There are no prerequisites courses for the student in order to select and attend the course. However, in order to better understand the course, students must have good knowledge of the compulsory course of the Department related to Bioinformatics, such as Biochemistry, Genetics, Cell Biology, Molecular Biology and Biophysics.

The course is offered to Erasmus students: Teaching in Greek language - Exams in English language.

The evaluation process is carried out in Greek language (there is the possibility in English for Erasmus students), with a final examination of the whole course that includes: Theory: Written examination with questions that demand extensive answer and b) multiple choice questions (50% of the total grade of the course), Practicals: Written examination (40%) with questions that demand extensive answer and evaluation of the written exercises (10%) that have been deposited after the end of each practical through the e-class platform (50% of the total grade of the course).

If you require more information, please contact the Course Coordinator, Assoc. Prof. Vassiliki A. Iconomidou at: Tel: +30-210 727 4871; Email: veconom[at]biol.uoa[dot]gr