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
Map Muthgasse (Google Maps)
Office hours during semesterMon to Thu, 4.30 p.m.-6.00 p.m.
By appointmentMon to Thu, 10.00 a.m.-6.00 p.m.Fri, 10.00 a.m.-1.00 p.m.
Application period for academic year 2022/23
1st January to 19th June 2022
tuition fee / semester:
+ ÖH premium + contribution2
1 Tuition fees for students from third countries € 727,- per semester
2 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: 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: Dr. Gerhard Dürnberger
Proteomics: opportunities and aims Methods, focussing on mass spectrometry Statistical methods for quality control, motivation for and building of public repositories Databases/ontologies Bioinformatic applications making use of large data sets
Lecture, working with computer
Lector: Eva Valerie Lehner, BSc, Dipl.-Ing. Dr. Alexandra Posekany
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: DI. Dr.techn. Dominik Ertl, FH-Prof. 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 exam Distance learning: Practical assignment
Lecture Student presentations followed by discussions Practical assignments in small groups Open distance learning
Lector: Dipl.-Ing. Barbara Lederer
Basic concepts of Data Mining Introduction into Visualization Pros 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 Dr. Gerhard Gaube
Extending the knowledge in the programming language Python in the context of real biological problems. * Functions * Container Classes (Listen, Dictionaries) * Object-orientated programming (Classes, Inheritance, ...) * File handling * Generators
Written exam at the end of the course and evaluation of the exercises
Lectures Homework Exercises
Lector: Ing. DI (FH) Nadine Elpida Tatto
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 in a combined log file (Prerequisite for exam admission).
Lecture and exercises during lecture time and at home
Lector: Dr. Christian Steineder
Introduction to algorithms, graph theory, basic common and bioinformatics algorithms
Discussion of the content illustrated with examples. Course material will be provided.
Lector: FH-Prof.in Mag.a Dr.in Alexandra Graf
1) Acquire knowledge on selected bioinformatics chapters (Short/long-read technologies, selected applications e.g. ChIP-Seq, RNA-Seq) and 2) the theoretical basics and application of relevant bioinformatics tools for the analysis of sequencing data
40 % Hands on exercise: Hand in a short program which solved a given task 20 % Moodle exam 40 % Journal Club: Presentation of a scientific paper in Groups
- Introductions and explanations (lecture) - Exercises using the computer
The exercise should give students the option of working with software and programs introduced in the lecture Transcriptomics and Genomics.
Practical examples, DataCamp courses
DataCamp, Moodle, Linux server, example scripts
Lector: Dipl.-Ing. Dr.techn. David Steyrl
Upon successful completion, students will have knowledge in: - historical outline of machine-learning development - key terms of the field (AI, ML, ...) - important concepts (bias-variance trade off, cross-validation, ...) - overview of important algorithms in the field - basic programming in python - application of ML algorithms to real-world data Every lesson of this seminar consists of two parts. The first half is spent on theory, whereas the second half is used to expand the theoretical knowledge by practical exercises in Python.
Written exam (multiple choice online in moodle, 30min). No aids are allowed to be used.
Lecture + Exercise: - Lecture: Hybrid: at the auditorium, online, videos on moodle - Exercise: Jupyter notebooks, solutions, online discussions of the exercises
Lector: FH-Prof.in Mag.a Dr.in Alexandra Graf, DI (FH) Anton Grünberg
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.
Seminar Talks 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 and participation) Distance learning: Practical assignment
Student presentations followed by discussions Practical assignments in small groups
Lector: Mag.rer.nat.Dr.rer.nat. Sophia Derdak, DDr. Alexander Tolios, BA MA MSc
-introduction in medical genome analysis -experimental design -quality evaluation of the raw data -variant classification -variant identification -variant annotation -gene expression analysis -interpretation of results -data protection
- presence and active participation - successful completion of the exercise modules - presentations of the results of the exercise modules by the students
- lecture on concepts with exercise modules - presentations of the results of the exercise by the students and discussion
General topics of statistics: statistical modeling, selection of models generalized models (logistic regression) bayesian estimate and modeling creation 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: FH-Prof.in Mag.a Dr.in Alexandra Graf, Ing. DI (FH) Dr. Harald Kühnel, MSc, Katharina Seiberl, BSc MSc, Monika Waldherr, MSc
-) Introduction to the Oxford Nanopore sequencing technology -) Sequencing of DNA samples using MinION in the wet lab -) Development of suitable quality control -) Development of suitable analysis pipeline -) Interpretation and discussion of results
Immanent examination, protocol of the results of the practical exercises, final exam
-) Presentation -) practical exercises in the wet-lab and in-silico
Form and features of the written thesis. Presentation techniques.
Talk - discussion
Lector: DI Christian Heiderer, Benedikt Singer
This course targets 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 QT Additional 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
Self-written programs at the middle and the end of the course
Presentations and discussions, hands-on practice on the PC, discussions.
Lector: Ing. Christian Binder, BSc, Martina Salzmann, BSc, BSc
- Introduction to programming using C/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, exercises, presentation, collaboration
- lecture - presentation and collaboration - practice during the lecture - exercises
Lector: Daniel Mitterecker, BSc, MSc, Smriti Shridhar, PhD
Part 1 Introduction to process automation. Understanding why and how automation of bioinformatics processes is done. Exploring state-of-the-art workflow management systems used in the field of bioinformatics. Part 2 Introduction to version control with Git. Utilization of container virtualization in bioinformatics. Introduction to Amazon Web Services (AWS).
Homework Written test at the end of the lecture. Project.
Lecture, example exercises. Home exercises to practice learned concepts.
Lector: FH-Prof. DI Dr. Michael Maurer, Laurentius Orsolic, BSc
As an example from biotechnology, students will work in the brew lab to create a beer, following a recipe. Students will be introduced into the topic of brewing and will have the chance to see an automated solution and investigate the data produced by the equipment. Additionally to the work in the lab, students are required to design a label for their beer and create a website with the recipes they worked on. The students will work in groups of 3-4 persons.
Students will be graded on their performance in the lab and the design of the label and web page.
Presentation, praktical lab exercise
Lector: Mag. Dipl.-Ing. Dr. Martin Pfeffer, Mag. Karin Pfeffer
"hands-on" priciples in business administration Development of a business plan
preparation & presentation of a business plan
Lector: Stefan Smyczko, MSc
FOCUS OF THE LECTURE ON: "SOFTWARE IN MEDICAL FIELD - SOFTWARE AS A MEDICAL DEVICE" To gain the essential know how on the topic "Software as a Medical Device". Insight into the legal basis for these kinds of products incl. definition and distinguishing it from other products; when is software a medical device? Which phases of development do exist, what has to be concerned when developing such product? Quality control and quality assurance as well as actual changes in the legal environment (MDR - Medical Device Regulation). Special focus is set on Validation of software as a medical device.
Presentation of the student and their evaluation as assessment
Introduction into the topic as lecture, followed by selected topics to be presented by the student on the last day of the lecture.
Lector: Dipl.-Ing. Dr. Gottfried Himmler
The Entrepreneur How do new things develop? Recipies for success? What is an enterprise? Systems theory perspective What is management? Entrepreneur versus Manager: Tasks Character The idea The Business Model The Business Plan The ideal Leader. Basics of Management. Tasks of Managers. Management Tools.
Lecture & Workshop
Lector: Smriti Shridhar, PhD
Understanding genetic diseases, biomarkers Genome wide association studies (GWAS) Interpreting DNA variants Human Genome Project Designing and Analyzing Clinical Trials in R
Multiple-Choice Questions in the middle of the course and scientific papers related to the topic will be presented by students (in groups) at the end of the course
Lecture / Practical exercises / Case-studies / Presentations
Introduction to the production and analysis of metagenome/microbiome data.
Practical exercise, presentation
Vortrag, Diskussion und praktische Beispiele.
Lector: Dr. Sven Brüschweiler, Dr. Leonhard Geist, Dr. Tanja Gesell
based on the class from last semester RNA and Protein Structure Prediction, this lecture addresses Molecular Design; topics include: - from small molecule descriptions to Protein - Ligand and RNA - Ligand complexes as well as Protein RNA interactions - high-throughput screening (HTS) - ncRNA in human diseases - pharmacophore models - disease networks
Practical sessions and a project at the end of the course (50% each)
Lector: Silvia Schmidt, BSc MSc
Internet survey Internet-of-Things / Biothings survey LoRaWAN Project IT-Security basics Genome browser basics
Written exam & practical exercises
lecture, exercises, inverted classroom
Lector: Dipl.-Ing. Anatol Dietl, Mag. iur. Dipl.-Ing. Dr. Dr. Michael Stadler
Protective rights; Reading patent documents; scope of protection; novelty, state of the art; inventive step; further requirements of patentability; patent application procedure; international patent laws and treatys; patent licensing;
written tests at the beginning of the lecture units; homework problem
Lector: Mag.rer.nat. David Ruckerbauer
Computer models of biochemical networks are able to connect the genotype with the phenotype. In this primer we will give an introduction to biochemical network analysis. We will introduce basic concepts of network reconstruction and constraint based analysis of biological networks. In particular we will cover the process of building (genome scale) metabolic models and study the steady state behavior of these networks with flux balance analysis (FBA) and related methods. Finally we will show that these methods are successfully used in metabolic engineering, where FBA is a standard approach for the rationally designing microbial cell factories. (*) Basic mathematical concepts in systems biology (*) Reconstruction of biochemical networks (*) Stoichiometric networks and their analysis (*) Applications in biotechnology
Home work and final exam
Lecture and in class exercises
Methodology for the implementation of the diploma thesis: clarification of the procedure through individual presentations of the thesis
Assessment of the presentation
Lector: FH-Prof. DI Dr. Michael Maurer
The content of this course is the writing of a diploma thesis.
The „written diploma thesis“ constitutes the result of the quality of the works conducted. For this reason, the assessment is based on the quality of the research as well as on the written presentation.
The diploma thesis has to be written in consultation with the FH supervisor and beforehand has to be approved by the head of the academic section.
In the course each student presents his/her Master thesis. Progression of the thesis and potential setbacks and problems will be discussed in the group.
Semester dates Winter semester: Mid of August to end of January Summer semester: Beginning of February to mid of July
Number of teaching weeks 20 per semester
Times 6.00 p.m.-9.15 p.m. (ca. four 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:
Regulation for the admission of third country citizens (PDF 223 KB)
Information for applicants with non-Austrian (school) certificates (PDF 145 KB)
To apply you will require the following documents:
Please note: 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 admission procedure consists of a written test and an interview with the admission committee.
The study places are awarded at the latest in mid-July based on this ranking. The process as a whole and all test and assessment results from the admission procedure are documented in a transparent and verifiable manner.
Written test and interview May and June
Planned start of the first semester Mid of August
If you have any questions regarding accessibility or if you have a specific need in the admission procedure due to an impairment, please contact Ursula Weilenmann for organizational reasons as early as possible at email@example.com.
Since we try to take into account individual needs due to disabilities when conducting the written admission test, we ask you to indicate in your online application to Weilenmann in which form you require support.
Your contact person in the department Gender & Diversity ManagementMag.a Ursula Weilenmannbarrierefrei@fh-campuswien.ac.athttp://www.fh-campuswien.ac.at/barrierefrei
Head of Degree Programs Bioengineering, Bioinformatics, Biotechnological Quality Management, Bioprocess Engineering T: +43 1 606 68 firstname.lastname@example.org
New study location from winter semester 2022/23 The Department of Applied Life Sciences will move to the new building at Favoritenstraße 222, 1100 Vienna in the summer of 2022.
We work closely with numerous industrial companies, universities such as the University of Natural Resources and Life Sciences, Vienna (BOKU), the Austrian Centre of Industrial Biotechnology (ACIB) and other research institutes. This guarantees you strong contacts for internships, employment 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!
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Information Folder Bioinformatics Master (PDF 80 KB)
Folder Applied Life Sciences (PDF 831 KB)