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Curriculum

The MSc program begins in the winter semester of each academic year.

To obtain the MSc degree, a total of one hundred twenty (120) credit units (ECTS) are required. The courses of the MSc program can be taught throughout an academic semester with fixed hours per week, or within a few weeks with a corresponding increase in the number of weekly hours. Courses may, on occasion, include laboratory exercises and/or seminars.

Teaching of the courses is conducted either in person or remotely, in accordance with current legislation and the provisions of Article 7 of this regulation.

During the course of their studies, graduate students are required to attend and successfully complete postgraduate courses as well as complete a postgraduate thesis.

The preparation of the postgraduate thesis takes place in the third and fourth semester of studies and is credited with forty-two (42) ECTS.

The language of instruction is Greek and, in some cases, English (e.g., invitation of foreign speakers), while the language of writing for the postgraduate thesis is either Greek or English.

For successful completion of the studies, each postgraduate student must attend, participate, and pass successfully in the eleven (11) mandatory courses offered by the MSc, two (2) elective courses, and the Postgraduate Thesis. Postgraduate students have the option to attend and be examined in all elective courses offered by the MSc; however, for calculation of the final grade, they must choose only two (2) of them and inform the Department Secretariat.

The elective courses may be modified annually in terms of both number and content and cannot be less than two (2).

Graduate students are informed about the content of the courses through this operating regulation and declare their preferences at the beginning of the third and fourth semester. There is no possibility of changing courses afterwards.

To conduct an elective course, a declaration from 30% of the students of the MSc is required for that specific year. The detailed curriculum of the courses (course titles, content, and instructors) is decided by the Steering Committee. Each course is assigned to one or more instructors, and a coordinator, who is a faculty member of the MSc, is appointed. The course material may be modified following the instructors’ proposal and the Steering Committee’s approval. Regular meetings of the participants in teaching courses of related academic subject matter are scheduled under the responsibility of the Director of the MSc, aiming to harmonize the content of each course.

Course Content/Description

A) Compulsory Courses

Molecular Biology and Genetics

The purpose of this course is to understand the basic concepts of Molecular Biology related to the flow of information and the nature of genetic material, as well as to understand mechanisms, with emphasis on regulatory phenomena. An additional goal is for students to learn the principles underlying the most important cutting-edge techniques in Molecular Biology and to understand the applications of these techniques in basic and applied research. Additionally, the course introduces students to the modern and rapidly evolving field of Genetics, particularly applications related to human health, biotechnology, and personalized medicine, helping them become familiar with the use of genetic databases and to reflect on the ethical and social dimensions of genetic research.

Biomolecular Structure and Function

The aim of this course is the study of the structure of biomolecules that constitute organisms and the understanding of how biomolecules interact with each other, forming organized supramolecular structures, undergoing structural changes, in order to interpret the properties and functions of organisms. The course focuses on protein architecture issues using principles of stereochemistry and stereodiagnostics analyses, utilizing real molecular models, and extends to stereochemical diseases-misfolding diseases related to incorrect protein folding. Furthermore, weak interactions and their role in protein folding are analyzed, as well as water structure, and issues of developing computational tools for studying and designing biomolecular complexes and biomaterials.

Programming Languages and Software Tools in Bioinformatics i

The purpose of this course is to understand the basic principles of programming languages and their use in developing programs to solve mathematical problems, as well as problems related to biological data. Within the course, the C and R programming languages are taught. During the learning process of the C programming language, topics of structured and modular programming are taught, the definition of variables and constants, as well as the use of unary and binary operators to form numerical, logical, and complex expressions. Memory management mechanisms are also analyzed, as well as the variables of a program. The main goal is the creation of complex data structures, as well as the design of autonomous programs by implementing communication methods of each program with the operating system in which it runs. Understanding and applying the above is achieved both at a theoretical and practical level through compulsory laboratory exercises.

The learning goal of the R statistical programming language is to learn and apply programming techniques to mathematical, statistical, and probability problems. Within the course, students become familiar with the R environment (commands, windows, menus), with numerical operations and representations in R, they learn the definition and management of objects, control and repetition commands, functions in R, and are trained in program development and construction of multiple graphs, taking into account modern data management problems in biology.

Statistics in Bioinformatics

The aim of this course is to acquire basic knowledge of statistical analysis for the appropriate selection of mathematical concepts through which medical-biological problems can be modeled, as well as the use of this knowledge in computer science applications. Fundamental methods of statistical analysis relevant to the methods of statistical analysis encountered in the foundation and application of computer science and data mining methods using appropriate machine learning algorithms are taught within the course. Furthermore, specific examples of applications in medical-biological issues are discussed, the use of new technologies with the help of programs such as Matlab, SPSS, R, and Weka.

Principles and Methods of Bioinformatics

The aim of the course is to understand the basic principles and methods of Bioinformatics and to demonstrate, both through lectures and through practical laboratory work, how Bioinformatics has differentiated the way modern research in the Biological Sciences is conducted. Within the course, students, after an analytical historical journey of the nascent field of Bioinformatics, come into contact with the use of molecular graphics programs, with the most important biological databases, with molecular anchoring methods, with the design of initiators for PCR reactions, and with the analysis of results -omics, with ontologies, the analysis of biological networks (graphs), artificial neural networks, hidden Markov models (HMM) and their applications in Bioinformatics.

Computational Analysis of Biomacromolecular Sequences

The aim of this course is to understand and become familiar with the basic concepts of Computational Analysis of Biomolecular Sequences not only in theory but also in practice. The student should be able to know the theory behind the basic relevant bioinformatics algorithms and be able to design their own. Within the framework of the course, topics such as multiple and pairwise sequence alignment, similarity searching in databases, protein and DNA prediction algorithms, prediction of protein secondary structure, genome analysis, sequence representation, as well as linguistic characteristics of genetic messages are analyzed.

Computational Analysis of Biomolecular Structures

The purpose of this course is to learn techniques and methods of Structural Bioinformatics for managing data concerning the structure and interactions of biomolecules and small molecules, which lead to specific biological responses/functions. Methods for determining and modeling the 3D structure of proteins as well as methods for determining their secondary structure are presented within the course. The basic principles and applications of Electron Microscopy (EM), Scanning Electron Microscopy (SEM), Cryo-electron microscopy, as well as integrated approaches of Structural Biology with applications in Health and Biotechnology are also discussed.

Programming Languages and Software Tools in Bioinformatics ii

The aim of the course is to complement the core knowledge of Bioinformatics-Computational Biology with two programming languages, Perl and Python, for solving complex bioinformatics problems, such as the analysis of biological networks, genomic analyses, gene expression analyses, sequence management problems, pattern searches, and sequence classification. Upon completion of the courses, students will be able to develop computational programs using both Perl and Python programming languages, both for implementing solutions to algorithmic problems with an emphasis on bioinformatics and for using machine learning libraries and deep neural networks for solving machine learning problems in the same scientific field.

Molecular Recognition – Molecular Diseases – Structural Drug Design

The purpose of the course is to provide a comprehensive presentation of the processes that make up the discovery and development of new drugs, with an emphasis on methodologies for rational design of small molecular weight biologically active molecules. The student is familiarized with the different scientific approaches applied in the successive stages of drug development and design, and the role and significance of each of these is taught for achieving the desired result. By the end of the period, the student will be able to develop critical thinking about the various factors that determine the overall value of the molecules under study as potential drugs, and to utilize it both in understanding their biological or therapeutic action and in managing fundamental research questions that may arise in their subsequent professional career.

Methodology of Research

The aim of the course is to provide knowledge related to the methodology of scientific research. It includes topics such as the principles of research methodology, writing, evaluation, and publication of research results in the scientific press, selection of scientific journals, use of bibliography management tools, structure of a research paper, evaluation of a paper using the peer review system, through which students can plan and conduct small or large-scale scientific research, evaluate and utilize research findings and data, and support their scientific research at the seminar level.

Application of Informatics in the Study and Preservation of Biodιversity

The purpose of the course is to study organism diversity, the distribution of organisms in space and time, the threats to biodiversity, methods of conservation, the ability to extract data from databases and libraries for effective biodiversity protection, the use of information systems in organizing and studying museum collections, and the design of sampling with new technologies (geospatial analysis, satellite imaging, small field recorders, etc.). The objectives of the course include acquiring knowledge about Earth’s biodiversity and specifically that of Greece, as well as studying diversity through bioinformatics applications.

Preparation of Master’s Thesis

The Master’s Thesis constitutes an independent scientific and systematic approach to analyzing a research question in the field of Bioinformatics – Computational Biology, and composing a solution, relying on existing literature and/or other research studies. The Master’s Thesis, conducted computationally, with in silico experiments, has a research, exploratory, developmental, or applied character. Its aim is to enable the graduate student to practice research methodology and address practical problems arising during its execution.

B) Elective Courses

Special Topics in Bioinformatics I

(Data Structures – Databases – Biological Database Design)

The aim of the course is to understand the basic ways of structuring data in memory as well as the basic principles of Databases, and to become familiar with the process of creating a database. Upon successful completion of the course, the student will be able to use the basic commands of the SQL language, create databases for storing biological data, and use appropriate data structures in memory for processing data extracted from a Database.

Special Topics in Bioinformatics II

(Internet Application Architecture and Bioinformatics)

The course focuses on designing and developing modern internet applications for bioinformatics with an emphasis on World Wide Web applications. It presents the architecture and infrastructure of the World Wide Web and client/server application architecture with an emphasis on the architecture of multi-layered World Wide Web applications. Topics covered include Web Server/Web Browser operation, HTTP protocol, HTML/CSS and Javascript/Typescript languages, relational database management systems on the internet (MySQL), backend technologies: Servlets, RESTful Web Services, Object-Relational Mapping, connection pools, frontend technologies: JSP, Javascript, Angular, and World Wide Web application architecture patterns (Model 1, Model-View-Controller).

Special Topics in Bioinformatics III

(Complex Biological Systems)

The aim of this course is twofold. On a theoretical level, it aims to familiarize students with the methods and techniques of the interdisciplinary field of complex adaptive systems as applied to dynamic modeling and theoretical study of a variety of biological problems at all levels of analysis, while offering a basic theoretical training enabling the identification of new problems amenable to this modeling and study approach. On a practical level, it aims to experiment with some systems or model some complex dynamic phenomena systematically investigate and evaluate alternative models and their respective results, both in terms of their substantive content and methodologically.

Special Topics in Bioinformatics IV

(Microarray Technologies and Applications)

The aim of the course is to familiarize students with the analysis of microarray and next-generation sequencing (NGS) data. Students will learn about various -omics fields and will mainly focus on transcriptomics. They will understand the principle of microarray technology and become acquainted with various individual technologies (e.g., single-channel and two-channel). They will learn about the structure of public repositories of transcriptomic data as well as their contents. They will study normalization algorithms for primary microarray data. They will become familiar with statistical analyses of basic approaches in transcriptomics (differential gene expression and co-expression analyses) and enrichment analyses of biological terms. In the laboratory course, students will see how the above are applied in practice.