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Semester A

Molecular Biology and Genomics

Semester: A’

Course Type: Compulsory

Course Curriculum

  • Structure and organization of prokaryotic and eukaryotic cells – DNA, Chromosomes – Transfer of sequential information (introductory concepts, aimed at educating students without a background in Biology, some concepts will be covered in greater detail).
  • Principles of DNA replication, replication origins and initiators, trans-factors, Principles of DNA Transcription, regulation of transcription in eukaryotes.
  • Genetic Code – structure and function of tRNAs and ribosomes in mRNA translation.
  • Principles of mRNA translation in prokaryotic and eukaryotic cells.
  • Recombinant DNA, molecular cloning  – Southern, Northern, DNA-sequencing, PCR.
  • Mechanims of DNA repair.
  • DNA-sequencing. Modern approaches and sequencing methods.
  • Sequence repeats – chromosome telomers – cell aging – cell lines – Model organisms.
  • Post-translational modifications – protein dissociation and proteolysis (proteasome and lysozomes)
  • The Human Genome Project – Genetic probes – microarray technologies.
  • Applications of DNA analysis in forensic sciences.
  • Genetically Modified Organisms, Methods – applications – risks
  • Animal Cloning, methods – applications – risks

Administrator

  • Prof. I. Trougakos

 

 Biomolecular Structure and Function

Semester: A’

Course Type: Compulsory

Course Curriculum

  • Atomic Representation of Molecular Structure.
  • Biological macromolecules: Structure and conformations, Non-bonded interactions and their importance, Biological macromolecules in aqueus and non aqueus environment, Structure Determination Methods, Crystal Symmetry.
  • Protein architecture: sequence, secondary structure, structure motifs, structural and functional domains, tertiary and quaternary structure, protein-protein interactions.
  • Membrane proteins: hydrophobicity, protein-lipid interactions, energy and signal transduction, molecular engines, examination of selected, “model” membrane protein structures: (e.g. Rhodopsin, Bacteriorhodopsin, Ion channels etc).
  • Structural and fibrous proteins, collagen, super-helices and coiled-coil structures, polymers, amyloid aggregates and amyloidoses, biopolymers and biomaterials.
  • DNA binding proteins, protein-DNA recognition and interactions in eukaryotic and prokaryotic cells, DNA structure and helicity, nucleosome structure.
  • Carbohydrates (chitin, cellulose), protein-carbohydrate interactions in complex systems (e.g. insect cuticle)
  • Protein mechanics, prediction of structure, modeling, rational protein design.
  • Protein folding and stability.
  • Structural genomics

Administrator

  • Assoc. Prof. V. Iconomidou

 

Programming Languages and Software Tools in Bioinformatics I

Semester: A’

Course Type: Compulsory

Course Curriculum

  • Introduction
  • Data Types: Fundamental data types, definition of octal and hexadecimal constants, types of variables, arrays and strings, enumeration constants.
  • Operators: Substitution operator, numeric operators, increment and decrement operators, comparison operators, Boolean logical operators, digital logical operators, hypothetical operator, explicit data type conversion- the cast operator, the sizeof operator, Priorities of operators, mixture of different data types in expressions.
  • Control Structures: if structure, while structure, for structure, switch/case structure, continue structure, goto structure, recursion
  • Pointers: Definition, pointer variables, applications, Dynamic memory allocation functions.
  • Derived data types: Data structures, Bit fields, Unions, Definition of new data type: typedef
  • The C pre-processor: Definition of constants: The #define directive, File inclusion: the #include directive, Conditional compilation
  • Input/Output and Library Functions: Input/Output functions, other library functions
  • The structure of C programs: Functions, Arguments of the main function
  • Applications (Simple Bioinformatics Programs)

Administrator

  • Assoc. Prof. V. Iconomidou

 

Statistics in Bioinformatics

Semester: A’

Course Type: Compulsory

Course Curriculum

  • Sample space and events.  Probability of events. Basic counting rules. Permutations, combinations. Conditional Probability. Theorem of total probability and Bayes’ theorem. Stochastic independence.
  • Random variable. Probability density function and Cumulative density function. Discrete random variables. Continuous random variables. Distribution of random variables. Mean and variance.
  • Discrete and continuous distributions. Univariate and Multivariate distributions.  Central Limit Theorem and applications.
  • Statistical tables.Measures of central tendency and variability. Coefficient of variation.
  • Introduction to the STATA statistical package.
  • Frequency distributions of qualitative and quantitative characteristics.  Hypothesis testing.
  • Parametric and non-parametric approaches ( t-test, Wilcoxon rank test κτλ). Type I and II error rates. 2×2 tables.
  • Comparison of mean value with a constant. Comparison between two mean values.  T-test, Paired T-test.
  • T-test and paired t-test using STATA.
  • Analysis of Variance (ANOVA) and linear regression. Multivarate Analysis. Pearson correlation coefficient.
  • ANOVA and linear regression using STATA.
  • Non parametric approaches: Sign test, Wilcoxon, Mann-Whitney and Kruskal – Wallis tests. Spearman correlation coefficient. Logistic regression.
  • Non parametric approaches and logistic regression using STATA.
  • Evaluation of laboratory/clinical/epidemiological data.

Administrator

  •  Prof. M. Filippakis

Principles and Methods in Bioinformatics

Semester: A’

Course Type: Compulsory

Course Curriculum

  • What is Bioinformatics – Basic Definitions
  • Principles of Informatics – Computer Applications in Biological Sciences
  • Biological Databases  – Annotation principles and limitations
  • Protein and Genome Information Resources and Analysis
  • Genome Projects
  • Principles of Protein folding
  • Protein-protein interactions – Metabolic pathways – protein self-assembly, structure and function
  • Large scale analysis problems – High throughput methods – Principles of Systems Biology – Challenges in experimental determination of protein structure and function – Structural Genomics
  • Computational Analyis as a means to unveil the relationship between sequence, structure and function
  • Data Base Management Systems
  • Principles of Data Mining
  • Introduction to Machine Learning Methods and Bioinformatics applications

Administrator

  • Assoc. Prof. V. Iconomidou