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BIOINFORMATICS

             
Compulsory/Elective Code Semester Lectures Practicals Credits ECTS
Elective 13A14 6th 3 Hrs/Wk 3 Hrs/Wk 4 5.5 
Aims:
 
 

Bioinformatics 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.

The aim of the course is to familiarize students with the concepts, tools and applications of Bioinformatics in order to address biological questions/problems.

 
Objectives:
 
 

At the end of the course students should be capable 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.

More specific, 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

 
Lectures:
 
 

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

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)

 
Practicals:
 
 

1. Introduction to Windows - Bioinformatics in the web - HTML and web pages – Literature search - Data mining from Biological Databases. 2. Introduction to Unix  (I) 3. Introduction to Unix  (II) 4. Protein and Nucleic acid Databases - Specialized Protein and Nucleic acid Databases - Analysis Tools of Nucleic acid and Protein Sequence and Structure Databases 5-8. Perl Programming for Biologists - Bioinformatics Applications 9. BLAST – FASTA -– CLUSTAL – Tools for similarity searches and multiple sequence alignments 10. Finding motifs and periodicities in Nucleic acid and Protein sequences 11. Prediction algorithms (Secondary structure, Structure and Topology of membrane proteins, Signal peptide, Subcellular location etc.) 12. Analysis of protein-protein interactions, protein networks and biological pathways 13. Simple applications of Neural networks and HMM’s in Bioinformatics

 
Instructors:
 
  Lectures: Vassiliki A. Iconomidou, Assistant Professor of Biophysics – Molecular Biophysics (Coordinator) - Ioannis P. Trougakos - Associate Professor of Cell Biology & Electron Microscopy - Dr. Zoi Litou, Laboratory Teaching Staff - Dr. Nikolaos Papandreou, Laboratory Teaching Staff - Dr. Athanassios D. Velentzas, Laboratory Teaching Staff - Dr. Ourania Konstanti, Laboratory Teaching Staff
 
  Practicals: Vassiliki A. Iconomidou, Assistant Professor of Biophysics – Molecular Biophysics - Dr. Zoi Litou, Laboratory Teaching Staff - Dr. Nikolaos Papandreou, Laboratory Teaching Staff
 
Notes:
 
 

The evaluation process is conducted in Greek (there is the possibility of examining in English for Erasmus students) during the Semester final exams and includes: Theory: Written examination with a) 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). The total score is the sum of the above individual evaluations.

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