Bioinformatics

Master, part-time

Overview

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.

Contact us

Contact us!

Elisabeth Beck
Elisabeth Holzmann, Bakk.techn.
Johanna Bauer
Barbara Philipp
Muthgasse 62
1190 Vienna
T: +43 1 606 68 77-3600
F: +43 1 606 68 77-3609
bioengineering@fh-campuswien.ac.at

Office hours during semester
Mon. to Thu. 4:30 p.m. to 6:00 p.m.

By appointment
Mon. to Thu. 10:00 a.m. to 6:00 p.m.
Fri. 10:00 a.m. to 1:00 p.m.

Stay up to date

Stay up to date!

Duration of course
4 Semester
Final degree
Master of Science in Engineering (MSc)
27Study places
120ECTS
Organisational form
part-time

The program starts every two years. Application period for the academic year 2020/21
1st January 2020 to 15th June 2020

tuition fee / semester:

€ 363,36*

+ 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)

What you can offer

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

What we offer you

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.

What makes this degree program special

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.

 

 


What you will learn in the degree program

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.

  • In applied informatics you will learn about programming, operating systems, networks and database systems. In order to effectively manage and evaluate data, you will acquire knowledge in mathematics, statistics, algorithms and software development.
  • In the field of molecular biology and biochemistry you will learn to conduct sequence comparisons and make structure and function predictions, as well as how high-throughput technologies function. Applied bioinformatics encompasses the application of bioinformatics and chemistry informatics.
  • Management and corporate management skills will round out your education.
  • You will apply the methods of scientific work within the framework of your master’s dissertation.

Curriculum

Lecture SWS ECTS
Databases VO

Databases VO

Lector: DI. Dr.techn. Dominik Ertl, FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka

2 SWS
4 ECTS

Lecture contents

•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

Assessment methods

Continuous assessments throughout the content presentation (grading of presentations)
Written exam
Distance learning: Practical assignment

Teaching methods

Lecture
Student presentations followed by discussions
Practical assignments in small groups
Open distance learning

Language

German

2 4
Selected chapters of Mathematics VO

Selected chapters of Mathematics VO

Lector: Univ.-Prof. Dipl.-Ing. Dr. Werner Timischl

1 SWS
2 ECTS

Lecture contents

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.

Assessment methods

Written examination

Teaching methods

Lecture combined with exercies.

1 2
Data Mining and Visualization ILV

Data Mining and Visualization ILV

Lector: Dipl.-Ing. Barbara Lederer

1 SWS
2 ECTS

Lecture contents

Basic concepts of Data Mining
Introduction into Visualization
Pros and Cons in representations

Assessment methods

The examination consists of attendance, active participation as well as the grading of the exercise work.

Teaching methods

Lecture plus exercise

Language

German-English

1 2
Introduction to Programming ILV

Introduction to Programming ILV

Lector: DI Norbert Auer, Josef Moser, BSc

2.5 SWS
5 ECTS

Lecture contents

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

Assessment methods

Written exam at the end of the course and evaluation of the exercises

Teaching methods

Lectures
Homework
Exercises

Language

German

2.5 5
Introduction to Linux and Shellscripting ILV

Introduction to Linux and Shellscripting ILV

Lector: Ing. DI (FH) Nadine Elpida Tatto, Anna Tomaselli, BSc

1 SWS
2 ECTS

Lecture contents

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.

Assessment methods

Written exam, complete and punctual delivery of exercises. Both count 50/50 for the grade

Teaching methods

Lecture and exercises during lecture time and at home

Language

German

1 2
Basics of Algorithms VO

Basics of Algorithms VO

Lector: Mag. Dr. Michael Wolfinger

1 SWS
2 ECTS

Lecture contents

Introduction to algorithms, graph theory, basic bioinformatics algorithms for predicting sequence similarity, alignments and RNA folding

Assessment methods

Written test, evaluation of practical tasks

Teaching methods

Slides and practical tasks

Language

German-English

1 2
Proteomics ILV

Proteomics ILV

Lector: Univ. Prof. Dr. Christopher Gerner

1.5 SWS
3 ECTS

Lecture contents

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

Assessment methods

written exam

Teaching methods

Lecture, working with computer

1.5 3
Sequence Comparison and Annotation VO

Sequence Comparison and Annotation VO

Lector: FH-Prof.in Mag.a Dr.in Alexandra Graf

1 SWS
2 ECTS

Lecture contents

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.

Assessment methods

The grade is composed of several parts:
30% - exercises in the lecture
70% - final exam

Teaching methods

Power point slides, discussions and practical exercises.

Language

German

1 2
Sequence Comparison and Annotation Practice ILV

Sequence Comparison and Annotation Practice ILV

Lector: Ing. DI (FH) Nadine Elpida Tatto

1 SWS
2 ECTS

Lecture contents

Hands-on to the topics of the lecture

Assessment methods

Exam at the end and punctual delivery of assigned homework.

Teaching methods

Examples are getting worked through in class and alone at home.

1 2
Statistics ILV

Statistics ILV

Lector: Dipl.-Ing. Dr. Alexandra Posekany, MMag. Sin-Yeung Yoo

1.5 SWS
3 ECTS

Lecture contents

introduction to statistics and probability using R; exploratory data analysis, statistical estimation, graphics, Bayes' theorem, important distributions, hypothesis testing, ANOVA and linear regression

Assessment methods

exercises, written exam, in calls participation

Teaching methods

lecture, presentation, work with PC, group work, exercises

1.5 3
Transcriptomics and Genomics ILV

Transcriptomics and Genomics ILV

Lector: FH-Prof.in Mag.a Dr.in Alexandra Graf, Dr.rer.nat. Markus Jaritz, Anna Tomaselli, BSc

1.5 SWS
3 ECTS

Lecture contents

1) Acquire knowledge on selected bioinformatics chapters (Next Generation Sequencing, ChIP-Seq, RNA-Seq) ans
2) Application of relevant bioinformatics tools for the analysis of associated data
3) using script languages under Linux, such as Bash, awk and perl.

Assessment methods

40 % Workshop: Hand in a short program which solved a given task
60% Lecture: Written exam

Teaching methods

- Introductions and explanations (lecture)
- Exercises using the computer

Language

German

1.5 3

Lecture SWS ECTS
Algorithms Practice UE

Algorithms Practice UE

Lector: Mag. Dr. Michael Wolfinger

1.5 SWS
3 ECTS

Lecture contents

Application of the framework and concepts presented in the course "Grundlagen Algorithmen": Implementation of simple algorithms in Perl.

Assessment methods

Written examination

Teaching methods

Beamer slides

Language

German

1.5 3
Applied Programming VO

Applied Programming VO

Lector: Ing. Christian Binder, BSc

2.5 SWS
5 ECTS

Lecture contents

- 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

Assessment methods

recurring Tests and exercises

Teaching methods

- lecture & presentation
- practice during the lecture
- exercises

Language

German

2.5 5
Selected Chapters of Bioinformatics SE

Selected Chapters of Bioinformatics SE

Lector: FH-Prof.in Mag.a Dr.in Alexandra Graf, DI (FH) Anton Grünberg, DI Dr. nat. techn. Matthias Hackl

1 SWS
2 ECTS

Lecture contents

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.

Assessment methods

Written exam at the end of the course.

Teaching methods

Seminar
Talks and Discussions

Language

German-English

1 2
Database Systems ILV

Database Systems ILV

Lector: DI. Dr.techn. Dominik Ertl, FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka

1.5 SWS
3 ECTS

Lecture contents

- 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

Assessment methods

Continuous assessments throughout the course (grading of presentations)
Distance learning: Practical assignment

Teaching methods

Student presentations followed by discussions
Practical assignments in small groups

Language

German

1.5 3
Machine Learning Methods ILV

Machine Learning Methods ILV

Lector: Dipl.-Ing. Dr. Theresa Scharl-Hirsch

1 SWS
2 ECTS

Lecture contents

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.

Assessment methods

Practice sessions and a project at the end of the course (50% each)

Teaching methods

Lecture + Exercise

1 2
Medical Analysis of Genoms VO

Medical Analysis of Genoms VO

Lector: DI Dr. Albert Kriegner, DI(FH) Dr. Stephan Pabinger

1 SWS
2 ECTS

Lecture contents

-introduction in medical genome analysis
-quality evaluation of the data
-identification of variations
-annotation of variations
-interpretation of data
-methods for "genetic testing"

Assessment methods

- presence and active participation
- presentations done by the students

Teaching methods

- lecture with exercise
- presentations done by the students and discussion

Language

German

1 2
Software Development ILV

Software Development ILV

Lector: DI Christian Heiderer

2 SWS
4 ECTS

Lecture contents

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 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

Assessment methods

Small self-written program at end of course

Teaching methods

Presentations and discussions, hands-on practice on the PC, discussions.

Language

German-English

2 4
Specific Statistics Practice UE

Specific Statistics Practice UE

Lector: Dipl.-Ing. Dr. Alexandra Posekany, MMag. Sin-Yeung Yoo

1 SWS
2 ECTS

Lecture contents

General topics of statistics:
statistical modeling, selection of models
generalized models (logistic regression)
bayesian estimate and modeling
creation of interactive apllicatins with R Shiny

Assessment methods

continuous assessments throughout the course and final examination

Teaching methods

Applied practice with "R"

Language

German

1 2
Structure Prediction in Biopolymeres VO

Structure Prediction in Biopolymeres VO

Lector: Dr. Sven Brüschweiler, Dr. Tanja Gesell

1 SWS
2 ECTS

Lecture contents

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

Assessment methods

Practical sessions and a project at the end of the course (50% each).

Teaching methods

theoretical and practical exercises

Language

German-English

1 2
Systems Modelling LB

Systems Modelling LB

Lector: Dr. Jürgen Zanghellini

2 SWS
4 ECTS

Lecture contents

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.

Assessment methods

Continous assessments throughout the course

Teaching methods

practical approach (wet lab)

Language

German-English

2 4
Master Thesis Preparation SE

Master Thesis Preparation SE

Lector: FH-Prof.in Mag.a Dr.in Alexandra Graf

0.5 SWS
1 ECTS

Lecture contents

Form and features of the written thesis. Presentation techniques.

Assessment methods

-

Teaching methods

Talk - discussion

Language

German-English

0.5 1

Lecture SWS ECTS
Automation ILV 1 2
Biotechnological Seminar UE 0.5 1
Business Plan and Cost Accounting ILV 2 4
Computational Systems Biology ILV 1.5 3
Development of bioinformatical Workflows ILV 1.5 3
Good Clinical Practice and Pharmacovigilance VO 1 2
Innovation and Entrepreneurship ILV 1 2
Clinical Bioinformatics ILV 1.5 3
Metagenom Analysis ILV 1 2
Molecular Design ILV 1.5 3
Network and Internet Technologies ILV 1.5 3
Patenting ILV 1 2

Lecture SWS ECTS
Master Thesis Supervision MT 1 1
Master Thesis MT 0 28
Master Thesis Seminar SE 1 1

Semester dates
Summer semester 2019: 11th February to 12th July 2019
Winter semester 2019/20: 19th August 2019 to 1st February 2020

Number of teaching weeks20 per semester

 

 

Times
6:00 p.m. to 9:20 p.m. (ca. three times Mon to Fri), Sat ca. every two weeks
(all day)

Language of instruction
German


How you benefit

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:

  • Biotechnologische Forschungsunternehmen
  • Biopharmazeutische Industrie
  • Industrielle Biotechnologie
  • Medizinische und molekularbiologische Forschung
  • Bioinformatik-DienstleistungsanbieterInnen

Admission

Admission requirements

  • Bachelor degree in natural sciences-technology or similar qualification from an institute of higher education with a total of 180 ECTS credits

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.

Application

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:

  • Bachelor/diploma certificate or equivalent certificate from abroad

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.

  • List of courses completed or transcript
  • Letter of motivation
  • CV in table form

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 selection process

The selection process consists of a written test and an interview with the selection committee.

  • Aim
    The aim is to ensure places are offered to those persons who complete the multi-level selection process with the best results. The tests are designed to assess the skills needed for an applicant's chosen profession.
  • Procedure
    The written selection test assesses the applicant's knowledge of programming, molecular biology and statistics. Applicants then undergo a selection interview on the same day to provide a first impression of their personal aptitude. The qualities interviewers are looking for include professional motivation, an understanding of the profession, performance, time management.
    Points are assigned to each section of the test.
  • Criteria
    The criteria for acceptance are based solely on performance. The geographical origin of the applicant has no influence on the selection decision. The admission requirements must be met in all cases. Applicants are evaluated according to the following weighting system:
    > Written selection test (60%)
    > Selection interview (40%)

    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 selection process are documented in a transparent and verifiable manner.

Contact

Secretary's office

Elisabeth Beck
Elisabeth Holzmann, Bakk.techn.
Johanna Bauer
Barbara Philipp
Muthgasse 62
1190 Vienna
T: +43 1 606 68 77-3600
F: +43 1 606 68 77-3609
bioengineering@fh-campuswien.ac.at

Office hours during semester
Mon. to Thu. 4:30 p.m. to 6:00 p.m.

By appointment
Mon. to Thu. 10:00 a.m. to 6:00 p.m.
Fri. 10:00 a.m. to 1:00 p.m.

Teaching staff and research staff


Cooperations and Campusnetzwerk

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!

Campusnetzwerk