Bioinformatics develops algorithms and programs to simulate biochemical processes and analyze molecular data. It combines knowledge of biochemical and molecular biological processes in organisms in applied computer science and data management as well as analysis. As part of the system biology, bioinformatics supports both research as well as industrial development and production. Your education will provide you with excellent prospects at the interface between basic research and development.
Elisabeth BeckElisabeth Holzmann, Bakk.techn.Johanna BauerBarbara PhilippMuthgasse 621190 ViennaT: +43 1 606 68 77-3600F: +43 1 606 68 firstname.lastname@example.org
Office hours during semesterMon. to Thu. 4:30 p.m. to 6:00 p.m.
By appointmentMon. to Thu. 10:00 a.m. to 6:00 p.m.Fri. 10:00 a.m. to 1:00 p.m.
The program starts every two years. Application period for the academic year 2020/211st January 2020 to 15th June 2020
tuition fee / semester:
+ ÖH premium + contribution**
* Tuition fees for students from third countries € 727 per semester
**for additional study expenses (currently up to €83 depending on degree program and year)
You have a background in natural sciences, are enthusiastic about IT and already possess basic knowledge. You see your future in combining both and using your IT skills to process and analyze the flood of data in life sciences and present it optimally and understandably. You are an analytical and process-oriented thinker. You enjoy solution-oriented work at the interface between different disciplines. You want to achieve professional success working on projects in a team and are open to management responsibilities. You can also imagine providing independent services. Average English skills are expected. Language of instruction is German
Your education and research benefit from our close partnerships with the University of Natural Resources and Life Sciences, Vienna (BOKU) and the Vienna Institute of Biotechnology (VIBT), who share the campus with us, as well as our strong network in the industry. In addition to experts from the industry, researchers from the BOKU also teach in our degree program and contribute their application-oriented know-how. Selected courses are offered in English, the technical language of life sciences. We are currently building an IT infrastructure that should be available as an internet service for public researchers as well as our students. Numerous R&D projects in the degree program offer you the opportunity to work with cutting-edge applications and to make valuable contacts for your future career. Practical relevance is also guaranteed at our Campus Lecture evenings, which are open to all and feature contributions from prominent experts.
The degree program focuses on molecular biology and is tailored specifically to the needs of pharmaceutical production. Bioinformatics is already an indispensable research tool for biotechnological methods in order to cope with the flood of data in life sciences. The deciphering of the human genome in genomic research is only one possible application. The main goal is to develop new medications based on the analysis of human genes.Huge databases of active ingredients must be searched for suitable candidates. Bioinformatics methods also make it possible to optimize and individualize therapies through the comparison of entire genomes. These tasks are even many times more complex than the makeup of the DNA sequence and can only be solved with the help of bioinformatics. The need for bioinformaticians in the biotech industry is growing rapidly. With our production-oriented education, you will be highly sought after.
As an interdisciplinary science, bioinformatics provides solutions for biological issues by applying informatics methods. The program combines applied informatics, data management and data evaluation with molecular biology, biochemistry and bioinformatics.
Lector: DI. Dr.techn. Dominik Ertl, FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka
•Principles of architecture and database systems•Transaction concept and SQL-core•Entity Relationship (ER) Model•Relational Model•Relational database design•Database implementation with SQL-DDL•Practical design assignment in small groups
Continuous assessments throughout the content presentation (grading of presentations)Written examDistance learning: Practical assignment
LectureStudent presentations followed by discussionsPractical assignments in small groupsOpen distance learning
Lector: Univ.-Prof. Dipl.-Ing. Dr. Werner Timischl
1 Discrete mathematics: permutations and combinations, time complexity of algorithms, recursions.2 Matrices: First and Second Kind of Spatial Representation; calculations with vectors and matrices; systems of linear equations; eigenvalues and eigenvectors.3 Selected methods of multivariate statistics: hierarchical classification; principal component analysis.4 Markov-models: Markov-chains; Hidden-Markov-models.
Lecture combined with exercies.
Lector: Dipl.-Ing. Barbara Lederer
Basic concepts of Data MiningIntroduction into VisualizationPros and Cons in representations
The examination consists of attendance, active participation as well as the grading of the exercise work.
Lecture plus exercise
Lector: DI Norbert Auer, Josef Moser, BSc
Extending the knowledge in the programming language Python in the context of real biological problems.* Software tools: Git* Container Classes (Listen, Dictionaries)* Object-orientated programming (Classes, Inheritance, ...)* File handling* Generators* Special modules: Biopython
Written exam at the end of the course and evaluation of the exercises
Lector: Ing. DI (FH) Nadine Elpida Tatto, Anna Tomaselli, BSc
The operating system Linux is essential in bioinformatics. Basic knowledge in the use of Linux (Ubuntu) is assumed. The lecture focuses on shell scripting and the usage of sed and awk. The named tools will be used for the processing of typical file formats in bioinformatics.
Written exam, complete and punctual delivery of exercises. Both count 50/50 for the grade
Lecture and exercises during lecture time and at home
Lector: Mag. Dr. Michael Wolfinger
Introduction to algorithms, graph theory, basic bioinformatics algorithms for predicting sequence similarity, alignments and RNA folding
Written test, evaluation of practical tasks
Slides and practical tasks
Lector: Univ. Prof. Dr. Christopher Gerner
Proteomics: opportunities and aimsMethods, focussing on mass spectrometryStatistical methods for quality control, motivation for and building of public repositoriesDatabases/ontologiesBioinformatic applications making use of large data sets
Lecture, working with computer
Lector: FH-Prof.in Mag.a Dr.in Alexandra Graf
The course deals with the analysis of biological sequence data. Starting from a genome sequence of an unannotated organism, we will try to determine the gene content and their function. During this process the students will work with a variety of available bioinformatics software but will also work on their own scripts to analyze the provided data.
The grade is composed of several parts:30% - exercises in the lecture70% - final exam
Power point slides, discussions and practical exercises.
Lector: Ing. DI (FH) Nadine Elpida Tatto
Hands-on to the topics of the lecture
Exam at the end and punctual delivery of assigned homework.
Examples are getting worked through in class and alone at home.
Lector: Dipl.-Ing. Dr. Alexandra Posekany, MMag. Sin-Yeung Yoo
introduction to statistics and probability using R; exploratory data analysis, statistical estimation, graphics, Bayes' theorem, important distributions, hypothesis testing, ANOVA and linear regression
exercises, written exam, in calls participation
lecture, presentation, work with PC, group work, exercises
Lector: FH-Prof.in Mag.a Dr.in Alexandra Graf, Dr.rer.nat. Markus Jaritz, Anna Tomaselli, BSc
1) Acquire knowledge on selected bioinformatics chapters (Next Generation Sequencing, ChIP-Seq, RNA-Seq) ans2) Application of relevant bioinformatics tools for the analysis of associated data3) using script languages under Linux, such as Bash, awk and perl.
40 % Workshop: Hand in a short program which solved a given task60% Lecture: Written exam
- Introductions and explanations (lecture)- Exercises using the computer
Application of the framework and concepts presented in the course "Grundlagen Algorithmen": Implementation of simple algorithms in Perl.
Lector: Ing. Christian Binder, BSc
- Introduction to programming using C++ with Linux- Usage of Compilers and Debuggers- Implementation of Examples- Excursus into object-oriented Progamming and high Performance computing- From the basic idea to the implementation
recurring Tests and exercises
- lecture & presentation- practice during the lecture- exercises
Lector: FH-Prof.in Mag.a Dr.in Alexandra Graf, DI (FH) Anton Grünberg, DI Dr. nat. techn. Matthias Hackl
The seminar is meant to give students an overview over the various fields of bioinformatics. Experts from different fields will be invited to talk about their experiences and projects.
Written exam at the end of the course.
SeminarTalks and Discussions
- Database query with SQL- Persistency problems, database programming, cursor concept- Elaborating the requirements and needs for computer scientists that use database systems and focuse on Bio-informatics - Programming with Perl: Perl-DBI, CGI- Practical Programming tasks in small groups
Continuous assessments throughout the course (grading of presentations)Distance learning: Practical assignment
Student presentations followed by discussionsPractical assignments in small groups
Lector: Dipl.-Ing. Dr. Theresa Scharl-Hirsch
This lecture gives an introduction to statistical data analysis using the statistical computing language R with an emphasis on machine learning methods applied to biological work. The topics include regression, cluster analysis and classification as well as the application of statistical models and tests using R including graphical data visualization. The machine learning methods presented include pricipal component analysis, partial least squares, random forests, support vector machines and neural networks.
Practice sessions and a project at the end of the course (50% each)
Lecture + Exercise
Lector: DI Dr. Albert Kriegner, DI(FH) Dr. Stephan Pabinger
-introduction in medical genome analysis-quality evaluation of the data-identification of variations-annotation of variations-interpretation of data-methods for "genetic testing"
- presence and active participation- presentations done by the students
- lecture with exercise- presentations done by the students and discussion
Lector: DI Christian Heiderer
This course looks at the basics of programming in C++.After repeating the basic language constructs of C we will shortly focus on working with arrays, pointers and references. Switching to C++, we will learn through hands-on programming effective application of following important fields: - Usage of the C++ Standard Library: Strings and container classes/templates - Data modelling with C++ classes - Implementation of Graphical User Interfaces (GUI) using QTAdditional non-C++ related targets are: - Understanding of the Software Development Process - Efficient work in small software projects - Writing easy-to-read and easy-to-maintain code
Small self-written program at end of course
Presentations and discussions, hands-on practice on the PC, discussions.
General topics of statistics:statistical modeling, selection of modelsgeneralized models (logistic regression)bayesian estimate and modelingcreation of interactive apllicatins with R Shiny
continuous assessments throughout the course and final examination
Applied practice with "R"
Lector: Dr. Sven Brüschweiler, Dr. Tanja Gesell
This lecture gives an introduction to basic principles of protein and RNA structure using top-down and bottom-up approaches for structure predictions. Topics include: - Introduction of experimental structure determination methods of biopolymers - Alignment methods and programs for structure prediction methods- In silicon prediction of RNA structure using dynamic programming - Genome wides screens of RNA structure - In silicon prediction of protein secondary and tertiary structure - Visualisations of RNA and Protein structures
Practical sessions and a project at the end of the course (50% each).
theoretical and practical exercises
Lector: Dr. Jürgen Zanghellini
At a practical approach (wet lab) the effect of perturbing a cell at a systems biology context is analyzed and transferred to a metabolic model. Thereby prospects and limitations of systembiology are demonstratively acquired.
Continous assessments throughout the course
practical approach (wet lab)
Form and features of the written thesis. Presentation techniques.
Talk - discussion
Semester datesSummer semester 2019: 11th February to 12th July 2019Winter semester 2019/20: 19th August 2019 to 1st February 2020
Number of teaching weeks20 per semester
Times6:00 p.m. to 9:20 p.m. (ca. three times Mon to Fri), Sat ca. every two weeks (all day)
Language of instruction German
As an expert in bioinformatics, you will manage and analyze data with high-throughput analysis methods and model structures and functions of biomolecules. You will find a career in the following occupational fields:
With at least > 13 ECTS credits in computer science, such as Introduction to Bioinformatics, Basics databases and operating systems, programming. > 13 ECTS credits in technical subjects such as process engineering, principals of bioprocess technology, measurement and control technology. More information is available upon request.
Equivalence is determined by international agreements, validation or in individual cases a decision by the head of the academic section.
There are 18 places available in the master's degree program in Bioinformatics every two years. The ratio of places to applicants is currently around 1:1.5
To apply you will require the following documents:
Certificates from abroad as well as a description of the courses and exemplary documents must be submitted as certified translations. Letters of recommendation from teachers from the institute abroad will help the head of the academic section to assess whether the admission requirements have been fulfilled.
It is not possible to save incomplete online applications. You must complete your application in one session. Your application will be valid as soon as you upload all of the required documents and certificates. In the event that some documents (e.g. references) are not available at the time you apply, you may submit these later via email, mail or in person by no later than the start of the degree program.
The selection process consists of a written test and an interview with the selection committee.
Head of Degree Program Bioengineering, Bioinformatics, Biotechnological Quality Management, Bioprocess Engineering T: +43 1 606 68 77-3601 email@example.com
We work closely with numerous industrial companies, universities such as the University of Natural Resources and Life Sciences, Vienna (BOKU) and the associated Vienna Institute of Biotechnology (VIBT) and other research institutes. This guarantees you strong contacts for your professional career or participation in research and development activities. You can find information about our cooperation activities and much more at Campusnetzwerk. It’s well worth visiting the site as it may direct you to a new job or interesting event held by our cooperation partners!