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.Apply nowContact usContact us!Elisabeth BeckElisabeth Holzmann, Bakk.techn.Johanna BauerBarbara PhilippMuthgasse 621190 ViennaT:+43 1 606 68 77-3600F: +43 1 606 68 77-3609bioengineering@fh-campuswien.ac.atMap 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.Duration of course4 SemestersOrganisational formpart-time120ECTSLanguage of instruction German22Study placesFinal degreeMaster of Science in Engineering (MSc)Application period for academic year 2022/231st January to 15th June 2022 tuition fee / semester:€ 363,361+ 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) 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 1. Semesters LectureSWSECTSSelected chapters of Mathematics VOSelected chapters of Mathematics VOLector: Univ.-Prof. Dipl.-Ing. Dr. Werner Timischl1SWS2ECTSLecture contents1 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 methodsWritten examinationTeaching methodsLecture combined with exercies.12Proteomics ILVProteomics ILVLector: Univ. Prof. Dr. Christopher Gerner1.5SWS3ECTSLecture contentsProteomics: 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 setsAssessment methodswritten examTeaching methodsLecture, working with computer1.53Statistics ILVStatistics ILVLector: Eva Valerie Lehner, BSc, Dipl.-Ing. Dr. Alexandra Posekany1.5SWS3ECTSLecture contentsintroduction to statistics and probability using R; exploratory data analysis, statistical estimation, graphics, Bayes' theorem, important distributions, hypothesis testing, ANOVA and linear regressionAssessment methodsexercises, written exam, in calls participationTeaching methodslecture, presentation, work with PC, group work, exercises1.53Databases VODatabases VOLector: DI. Dr.techn. Dominik Ertl, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka2SWS4ECTSLecture 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 groupsAssessment methodsContinuous assessments throughout the content presentation (grading of presentations) Written exam Distance learning: Practical assignmentTeaching methodsLecture Student presentations followed by discussions Practical assignments in small groups Open distance learningLanguageGerman24Data Mining and Visualization ILVData Mining and Visualization ILVLector: Dipl.-Ing. Barbara Lederer1SWS2ECTSLecture contentsBasic concepts of Data Mining Introduction into Visualization Pros and Cons in representationsAssessment methodsThe examination consists of attendance, active participation as well as the grading of the exercise work.Teaching methodsLecture plus exerciseLanguageGerman-English12Introduction to Programming ILVIntroduction to Programming ILVLector: DI Norbert Auer, DI Dr. Gerhard Gaube2.5SWS5ECTSLecture contentsExtending 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 * GeneratorsAssessment methodsWritten exam at the end of the course and evaluation of the exercisesTeaching methodsLectures Homework ExercisesLanguageGerman2.55Introduction to Linux and Shellscripting ILVIntroduction to Linux and Shellscripting ILVLector: Ing. DI (FH) Nadine Elpida Tatto1SWS2ECTSLecture contentsThe 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 methodsWritten exam, complete and punctual delivery of exercises in a combined log file (Prerequisite for exam admission).Teaching methodsLecture and exercises during lecture time and at home12Basics of Algorithms VOBasics of Algorithms VOLector: Dr. Christian Steineder1SWS2ECTSLecture contentsIntroduction to algorithms, graph theory, basic common and bioinformatics algorithmsAssessment methodsFinal projectTeaching methodsDiscussion of the content illustrated with examples. Course material will be provided.LanguageGerman-English12Transcriptomics and Genomics ILVTranscriptomics and Genomics ILVLector: FH-Prof.in Mag.a Dr.in Alexandra Graf, Eric Schinogl, BSc2SWS4ECTSLecture contents1) 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 methods40 % Hands on exercise: Hand in a short program which solved a given task 60% Lecture: Written examTeaching methods- Introductions and explanations (lecture) - Exercises using the computerLanguageGerman24Transcriptomics and Genomics Practice UETranscriptomics and Genomics Practice UELector: FH-Prof.in Mag.a Dr.in Alexandra Graf, Eric Schinogl, BSc1.5SWS3ECTSLecture contentsThe exercise should give students the option of working with software and programs introduced in the lecture Transcriptomics and Genomics.Assessment methodsPractical examplesTeaching methodsMoodle, Linux server, example scriptsLanguageGerman1.53 2. Semesters LectureSWSECTSMachine Learning Methods ILVMachine Learning Methods ILVLector: Dipl.-Ing. Dr.techn. David Steyrl1SWS2ECTSLecture contentsUpon 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.Assessment methodsWritten exam (multiple choice online in moodle, 30min). No aids are allowed to be used.Teaching methodsLecture + Exercise: - Lecture: Hybrid: at the auditorium, online, videos on moodle - Exercise: Jupyter notebooks, solutions, online discussions of the exercisesLanguageEnglish12Selected Chapters of Bioinformatics SESelected Chapters of Bioinformatics SELector: FH-Prof.in Mag.a Dr.in Alexandra Graf, DI (FH) Anton Grünberg1SWS2ECTSLecture contentsThe 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 methodsWritten exam at the end of the course.Teaching methodsSeminar Talks and DiscussionsLanguageGerman-English12Database Systems ILVDatabase Systems ILVLector: DI. Dr.techn. Dominik Ertl, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka1.5SWS3ECTSLecture 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 groupsAssessment methodsContinuous assessments throughout the course (grading of presentations and participation) Distance learning: Practical assignmentTeaching methodsStudent presentations followed by discussions Practical assignments in small groupsLanguageGerman1.53Medical Analysis of Genoms VOMedical Analysis of Genoms VOLector: Mag.rer.nat.Dr.rer.nat. Sophia Derdak, DDr. Alexander Tolios, BA MA MSc1SWS2ECTSLecture contents-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 protectionAssessment methods- presence and active participation - successful completion of the exercise modules - presentations of the results of the exercise modules by the studentsTeaching methods- lecture on concepts with exercise modules - presentations of the results of the exercise by the students and discussionLanguageGerman12Specific Statistics Practice UESpecific Statistics Practice UELector: Eva Valerie Lehner, BSc, Dipl.-Ing. Dr. Alexandra Posekany1SWS2ECTSLecture contentsGeneral topics of statistics: statistical modeling, selection of models generalized models (logistic regression) bayesian estimate and modeling creation of interactive apllicatins with R ShinyAssessment methodscontinuous assessments throughout the course and final examinationTeaching methodsApplied practice with "R"LanguageGerman12Structure Prediction in Biopolymeres VOStructure Prediction in Biopolymeres VOLector: Dr. Sven Brüschweiler, Dr. Tanja Gesell1SWS2ECTSLecture contentsThis 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 structuresAssessment methodsPractical sessions and a project at the end of the course (50% each).Teaching methodstheoretical and practical exercisesLanguageGerman-English12Data Analysis Laboratory LBData Analysis Laboratory LBLector: FH-Prof.in Mag.a Dr.in Alexandra Graf, Ing. DI (FH) Dr. Harald Kühnel, MSc, Katharina Seiberl, BSc MSc, Monika Waldherr, MSc2SWS4ECTSLecture contents-) 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 resultsAssessment methodsImmanent examination, protocol of the results of the practical exercises, final examTeaching methods-) Presentation -) practical exercises in the wet-lab and in-silicoLanguageGerman24Master Thesis Preparation SEMaster Thesis Preparation SELector: FH-Prof.in Mag.a Dr.in Alexandra Graf0.5SWS1ECTSLecture contentsForm and features of the written thesis. Presentation techniques.Assessment methods-Teaching methodsTalk - discussionLanguageGerman-English0.51Softwaredevelopment ILVSoftwaredevelopment ILVLector: DI Christian Heiderer, Benedikt Singer3SWS6ECTSLecture contentsThis 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 codeAssessment methodsSelf-written programs at the middle and the end of the courseTeaching methodsPresentations and discussions, hands-on practice on the PC, discussions.LanguageGerman-English36Applied Programming Practice ILVApplied Programming Practice ILVLector: Ing. Christian Binder, BSc, Martina Salzmann, BSc, BSc3SWS6ECTSLecture contents- 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 implementationAssessment methodsrecurring tests, exercises, presentation, collaborationTeaching methods- lecture - presentation and collaboration - practice during the lecture - exercisesLanguageGerman36 3. Semesters LectureSWSECTSAutomation ILVAutomation ILVLector: Daniel Mitterecker, BSc, MSc, Smriti Shridhar, PhD3SWS6ECTSLecture contentsPart 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).Assessment methodsHomework Written test at the end of the lecture. Project.Teaching methodsLecture, example exercises. Home exercises to practice learned concepts.LanguageGerman-English36Biotechnological Seminar SEBiotechnological Seminar SELector: Ing. Michael Geissler, MSc., FH-Prof.in Mag.a Dr.in Alexandra Graf, FH-Prof. DI Dr. Michael Maurer, Katharina Seiberl, BSc MSc0.5SWS1ECTSLecture contentsAs 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.Assessment methodsStudents will be graded on their performance in the lab and the design of the label and web page.Teaching methodsPresentation, praktical lab exerciseLanguageGerman0.51Business Plan and Cost Accounting ILVBusiness Plan and Cost Accounting ILVLector: Mag. Dipl.-Ing. Dr. Martin Pfeffer, Mag. Karin Pfeffer2SWS4ECTSLecture contents"hands-on" priciples in business administration Development of a business planAssessment methodspreparation & presentation of a business planTeaching methodslecture, WorkshopLanguageGerman24Validification of Software and Medical Devices VOValidification of Software and Medical Devices VOLector: Stefan Smyczko, MSc1SWS2ECTSLecture contentsFOCUS 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.Assessment methodsPresentation of the student and their evaluation as assessmentTeaching methodsIntroduction into the topic as lecture, followed by selected topics to be presented by the student on the last day of the lecture.LanguageGerman-English12Innovation and Entrepreneurship ILVInnovation and Entrepreneurship ILVLector: Dipl.-Ing. Dr. Gottfried Himmler1SWS2ECTSLecture contentsThe 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.Assessment methodsOralTeaching methodsLecture & WorkshopLanguageGerman12Clinical Bioinformatics ILVClinical Bioinformatics ILVLector: Smriti Shridhar, PhD1.5SWS3ECTSLecture contentsUnderstanding genetic diseases, biomarkers Genome wide association studies (GWAS) Interpreting DNA variants Human Genome Project Designing and Analyzing Clinical Trials in RAssessment methodsMultiple-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 courseTeaching methodsLecture / Practical exercises / Case-studies / PresentationsLanguageEnglish1.53Metagenom Analysis ILVMetagenom Analysis ILVLector: FH-Prof.in Mag.a Dr.in Alexandra Graf1SWS2ECTSLecture contentsIntroduction to the production and analysis of metagenome/microbiome data.Assessment methodsPresentation of a practical task.Teaching methodsVortrag, Diskussion und praktisches Beispiel.LanguageGerman-English12Molecular Design ILVMolecular Design ILVLector: Dr. Sven Brüschweiler, Dr. Leonhard Geist, Dr. Tanja Gesell1.5SWS3ECTSLecture contentsbased 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 networksAssessment methodsPractical sessions and a project at the end of the course (50% each)Teaching methodstheoretical and practical exercises1.53Network and Internet Technologies ILVNetwork and Internet Technologies ILVLector: Silvia Schmidt, BSc MSc1SWS2ECTSLecture contentsInternet survey Internet-of-Things / Biothings survey LoRaWAN Project IT-Security basics Genome browser basicsAssessment methodsWritten exam & practical exercisesTeaching methodslecture, exercises, inverted classroomLanguageGerman12Patenting ILVPatenting ILVLector: Dipl.-Ing. Anatol Dietl, Mag. iur. Dipl.-Ing. Dr. Dr. Michael Stadler1SWS2ECTSLecture contentsProtective 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;Assessment methodswritten tests at the beginning of the lecture units; homework problemTeaching methodsLectureLanguageGerman12Computational Systems Biology ILVComputational Systems Biology ILVLector: Mag.rer.nat. David Ruckerbauer1.5SWS3ECTSLecture contentsComputer 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 biotechnologyAssessment methodsHome work and final examTeaching methodsLecture and in class exercisesLanguageGerman-English1.53 4. Semesters LectureSWSECTSMaster Thesis Supervision APMaster Thesis Supervision APLector: FH-Prof.in Mag.a Dr.in Alexandra Graf0SWS1ECTSLecture contentsMethodology for the implementation of the diploma thesis: clarification of the procedure through individual presentations of the thesisAssessment methodsAssessment of the presentationTeaching methodsPresentationsLanguageGerman01Master Thesis MTMaster Thesis MTLector: FH-Prof. DI Dr. Michael Maurer0SWS28ECTSLecture contentsThe content of this course is the writing of a diploma thesis.Assessment methodsThe „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.Teaching methodsThe 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.LanguageGerman028Master Thesis Seminar SEMaster Thesis Seminar SELector: FH-Prof.in Mag.a Dr.in Alexandra Graf1SWS1ECTSLecture contentsIn the course each student presents his/her Master thesis. Progression of the thesis and potential setbacks and problems will be discussed in the group.Assessment methodsPresentationTeaching methodsPresentation, discussionLanguageGerman11Semester dates Winter semester: Mid of August to end of January Summer semester: Beginning of February to mid of JulyNumber 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 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 ForschungsunternehmenBiopharmazeutische IndustrieIndustrielle Biotechnologie Medizinische und molekularbiologische ForschungBioinformatik-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.Equivalent certification from abroad Equivalence is determined by international agreements, validation or in individual cases a decision by the head of the academic section.Regulation for the admission of third country citizens (PDF 223 KB)Information for applicants with non-Austrian (school) certificates (PDF 145 KB) Application To apply you will require the following documents:Proof of identity (copy of passport or copy of identity card)In case German is not your first language: Proof of German language skills at level C1Bachelor/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 transcriptLetter of motivationCV in table formPlease 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. Admission procedure The admission procedure consists of a written test and an interview with the admission committee.Aim The aim is to ensure places are offered to those persons who complete the multi-level admission procedure with the best results. The tests are designed to assess the skills needed for an applicant's chosen profession.Procedure The written admission test assesses the applicant's knowledge of programming, molecular biology and statistics. Applicants then undergo an admission 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 admission decision. The admission requirements must be met in all cases. Applicants are evaluated according to the following weighting system: Written admission test (60%)Admission 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 admission procedure are documented in a transparent and verifiable manner. Dates Written test and interview May and JunePlanned start of the first semester Mid of August Studying with disabilities 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 barrierefrei@fh-campuswien.ac.at.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 Contact > FH-Prof. DI Dr. Michael Maurer Head of Degree Program Bioengineering, Bioinformatics, Biotechnological Quality Management, Bioprocess Engineering T: +43 1 606 68 77-3601michael.maurer@fh-campuswien.ac.at Secretary's office Elisabeth BeckElisabeth Holzmann, Bakk.techn.Johanna BauerBarbara PhilippMuthgasse 621190 ViennaT:+43 1 606 68 77-3600F: +43 1 606 68 77-3609bioengineering@fh-campuswien.ac.atMap 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.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. Teaching staff and research staff > FH-Prof. Mag. Dr. Alexandra Graf Research Staff> Ing. DI (FH) Dr. Harald Kühnel, MSc Academic Staff> Monika Waldherr, MSc 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), 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! Welcome to our Campusnetzwerk Find suitable job offers, build valuable mentoring relationships and expand your professional network - become part of our community!Register now for free Downloads and Links Information Folder Bioinformatics Master (PDF 80 KB)Folder Applied Life Sciences (PDF 831 KB)
1. Semesters LectureSWSECTSSelected chapters of Mathematics VOSelected chapters of Mathematics VOLector: Univ.-Prof. Dipl.-Ing. Dr. Werner Timischl1SWS2ECTSLecture contents1 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 methodsWritten examinationTeaching methodsLecture combined with exercies.12Proteomics ILVProteomics ILVLector: Univ. Prof. Dr. Christopher Gerner1.5SWS3ECTSLecture contentsProteomics: 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 setsAssessment methodswritten examTeaching methodsLecture, working with computer1.53Statistics ILVStatistics ILVLector: Eva Valerie Lehner, BSc, Dipl.-Ing. Dr. Alexandra Posekany1.5SWS3ECTSLecture contentsintroduction to statistics and probability using R; exploratory data analysis, statistical estimation, graphics, Bayes' theorem, important distributions, hypothesis testing, ANOVA and linear regressionAssessment methodsexercises, written exam, in calls participationTeaching methodslecture, presentation, work with PC, group work, exercises1.53Databases VODatabases VOLector: DI. Dr.techn. Dominik Ertl, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka2SWS4ECTSLecture 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 groupsAssessment methodsContinuous assessments throughout the content presentation (grading of presentations) Written exam Distance learning: Practical assignmentTeaching methodsLecture Student presentations followed by discussions Practical assignments in small groups Open distance learningLanguageGerman24Data Mining and Visualization ILVData Mining and Visualization ILVLector: Dipl.-Ing. Barbara Lederer1SWS2ECTSLecture contentsBasic concepts of Data Mining Introduction into Visualization Pros and Cons in representationsAssessment methodsThe examination consists of attendance, active participation as well as the grading of the exercise work.Teaching methodsLecture plus exerciseLanguageGerman-English12Introduction to Programming ILVIntroduction to Programming ILVLector: DI Norbert Auer, DI Dr. Gerhard Gaube2.5SWS5ECTSLecture contentsExtending 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 * GeneratorsAssessment methodsWritten exam at the end of the course and evaluation of the exercisesTeaching methodsLectures Homework ExercisesLanguageGerman2.55Introduction to Linux and Shellscripting ILVIntroduction to Linux and Shellscripting ILVLector: Ing. DI (FH) Nadine Elpida Tatto1SWS2ECTSLecture contentsThe 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 methodsWritten exam, complete and punctual delivery of exercises in a combined log file (Prerequisite for exam admission).Teaching methodsLecture and exercises during lecture time and at home12Basics of Algorithms VOBasics of Algorithms VOLector: Dr. Christian Steineder1SWS2ECTSLecture contentsIntroduction to algorithms, graph theory, basic common and bioinformatics algorithmsAssessment methodsFinal projectTeaching methodsDiscussion of the content illustrated with examples. Course material will be provided.LanguageGerman-English12Transcriptomics and Genomics ILVTranscriptomics and Genomics ILVLector: FH-Prof.in Mag.a Dr.in Alexandra Graf, Eric Schinogl, BSc2SWS4ECTSLecture contents1) 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 methods40 % Hands on exercise: Hand in a short program which solved a given task 60% Lecture: Written examTeaching methods- Introductions and explanations (lecture) - Exercises using the computerLanguageGerman24Transcriptomics and Genomics Practice UETranscriptomics and Genomics Practice UELector: FH-Prof.in Mag.a Dr.in Alexandra Graf, Eric Schinogl, BSc1.5SWS3ECTSLecture contentsThe exercise should give students the option of working with software and programs introduced in the lecture Transcriptomics and Genomics.Assessment methodsPractical examplesTeaching methodsMoodle, Linux server, example scriptsLanguageGerman1.53
2. Semesters LectureSWSECTSMachine Learning Methods ILVMachine Learning Methods ILVLector: Dipl.-Ing. Dr.techn. David Steyrl1SWS2ECTSLecture contentsUpon 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.Assessment methodsWritten exam (multiple choice online in moodle, 30min). No aids are allowed to be used.Teaching methodsLecture + Exercise: - Lecture: Hybrid: at the auditorium, online, videos on moodle - Exercise: Jupyter notebooks, solutions, online discussions of the exercisesLanguageEnglish12Selected Chapters of Bioinformatics SESelected Chapters of Bioinformatics SELector: FH-Prof.in Mag.a Dr.in Alexandra Graf, DI (FH) Anton Grünberg1SWS2ECTSLecture contentsThe 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 methodsWritten exam at the end of the course.Teaching methodsSeminar Talks and DiscussionsLanguageGerman-English12Database Systems ILVDatabase Systems ILVLector: DI. Dr.techn. Dominik Ertl, FH-Prof. FH-Hon.Prof. Priv.-Doz. Mag. DI. DI. Dr.techn. Karl Michael Göschka1.5SWS3ECTSLecture 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 groupsAssessment methodsContinuous assessments throughout the course (grading of presentations and participation) Distance learning: Practical assignmentTeaching methodsStudent presentations followed by discussions Practical assignments in small groupsLanguageGerman1.53Medical Analysis of Genoms VOMedical Analysis of Genoms VOLector: Mag.rer.nat.Dr.rer.nat. Sophia Derdak, DDr. Alexander Tolios, BA MA MSc1SWS2ECTSLecture contents-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 protectionAssessment methods- presence and active participation - successful completion of the exercise modules - presentations of the results of the exercise modules by the studentsTeaching methods- lecture on concepts with exercise modules - presentations of the results of the exercise by the students and discussionLanguageGerman12Specific Statistics Practice UESpecific Statistics Practice UELector: Eva Valerie Lehner, BSc, Dipl.-Ing. Dr. Alexandra Posekany1SWS2ECTSLecture contentsGeneral topics of statistics: statistical modeling, selection of models generalized models (logistic regression) bayesian estimate and modeling creation of interactive apllicatins with R ShinyAssessment methodscontinuous assessments throughout the course and final examinationTeaching methodsApplied practice with "R"LanguageGerman12Structure Prediction in Biopolymeres VOStructure Prediction in Biopolymeres VOLector: Dr. Sven Brüschweiler, Dr. Tanja Gesell1SWS2ECTSLecture contentsThis 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 structuresAssessment methodsPractical sessions and a project at the end of the course (50% each).Teaching methodstheoretical and practical exercisesLanguageGerman-English12Data Analysis Laboratory LBData Analysis Laboratory LBLector: FH-Prof.in Mag.a Dr.in Alexandra Graf, Ing. DI (FH) Dr. Harald Kühnel, MSc, Katharina Seiberl, BSc MSc, Monika Waldherr, MSc2SWS4ECTSLecture contents-) 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 resultsAssessment methodsImmanent examination, protocol of the results of the practical exercises, final examTeaching methods-) Presentation -) practical exercises in the wet-lab and in-silicoLanguageGerman24Master Thesis Preparation SEMaster Thesis Preparation SELector: FH-Prof.in Mag.a Dr.in Alexandra Graf0.5SWS1ECTSLecture contentsForm and features of the written thesis. Presentation techniques.Assessment methods-Teaching methodsTalk - discussionLanguageGerman-English0.51Softwaredevelopment ILVSoftwaredevelopment ILVLector: DI Christian Heiderer, Benedikt Singer3SWS6ECTSLecture contentsThis 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 codeAssessment methodsSelf-written programs at the middle and the end of the courseTeaching methodsPresentations and discussions, hands-on practice on the PC, discussions.LanguageGerman-English36Applied Programming Practice ILVApplied Programming Practice ILVLector: Ing. Christian Binder, BSc, Martina Salzmann, BSc, BSc3SWS6ECTSLecture contents- 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 implementationAssessment methodsrecurring tests, exercises, presentation, collaborationTeaching methods- lecture - presentation and collaboration - practice during the lecture - exercisesLanguageGerman36
3. Semesters LectureSWSECTSAutomation ILVAutomation ILVLector: Daniel Mitterecker, BSc, MSc, Smriti Shridhar, PhD3SWS6ECTSLecture contentsPart 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).Assessment methodsHomework Written test at the end of the lecture. Project.Teaching methodsLecture, example exercises. Home exercises to practice learned concepts.LanguageGerman-English36Biotechnological Seminar SEBiotechnological Seminar SELector: Ing. Michael Geissler, MSc., FH-Prof.in Mag.a Dr.in Alexandra Graf, FH-Prof. DI Dr. Michael Maurer, Katharina Seiberl, BSc MSc0.5SWS1ECTSLecture contentsAs 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.Assessment methodsStudents will be graded on their performance in the lab and the design of the label and web page.Teaching methodsPresentation, praktical lab exerciseLanguageGerman0.51Business Plan and Cost Accounting ILVBusiness Plan and Cost Accounting ILVLector: Mag. Dipl.-Ing. Dr. Martin Pfeffer, Mag. Karin Pfeffer2SWS4ECTSLecture contents"hands-on" priciples in business administration Development of a business planAssessment methodspreparation & presentation of a business planTeaching methodslecture, WorkshopLanguageGerman24Validification of Software and Medical Devices VOValidification of Software and Medical Devices VOLector: Stefan Smyczko, MSc1SWS2ECTSLecture contentsFOCUS 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.Assessment methodsPresentation of the student and their evaluation as assessmentTeaching methodsIntroduction into the topic as lecture, followed by selected topics to be presented by the student on the last day of the lecture.LanguageGerman-English12Innovation and Entrepreneurship ILVInnovation and Entrepreneurship ILVLector: Dipl.-Ing. Dr. Gottfried Himmler1SWS2ECTSLecture contentsThe 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.Assessment methodsOralTeaching methodsLecture & WorkshopLanguageGerman12Clinical Bioinformatics ILVClinical Bioinformatics ILVLector: Smriti Shridhar, PhD1.5SWS3ECTSLecture contentsUnderstanding genetic diseases, biomarkers Genome wide association studies (GWAS) Interpreting DNA variants Human Genome Project Designing and Analyzing Clinical Trials in RAssessment methodsMultiple-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 courseTeaching methodsLecture / Practical exercises / Case-studies / PresentationsLanguageEnglish1.53Metagenom Analysis ILVMetagenom Analysis ILVLector: FH-Prof.in Mag.a Dr.in Alexandra Graf1SWS2ECTSLecture contentsIntroduction to the production and analysis of metagenome/microbiome data.Assessment methodsPresentation of a practical task.Teaching methodsVortrag, Diskussion und praktisches Beispiel.LanguageGerman-English12Molecular Design ILVMolecular Design ILVLector: Dr. Sven Brüschweiler, Dr. Leonhard Geist, Dr. Tanja Gesell1.5SWS3ECTSLecture contentsbased 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 networksAssessment methodsPractical sessions and a project at the end of the course (50% each)Teaching methodstheoretical and practical exercises1.53Network and Internet Technologies ILVNetwork and Internet Technologies ILVLector: Silvia Schmidt, BSc MSc1SWS2ECTSLecture contentsInternet survey Internet-of-Things / Biothings survey LoRaWAN Project IT-Security basics Genome browser basicsAssessment methodsWritten exam & practical exercisesTeaching methodslecture, exercises, inverted classroomLanguageGerman12Patenting ILVPatenting ILVLector: Dipl.-Ing. Anatol Dietl, Mag. iur. Dipl.-Ing. Dr. Dr. Michael Stadler1SWS2ECTSLecture contentsProtective 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;Assessment methodswritten tests at the beginning of the lecture units; homework problemTeaching methodsLectureLanguageGerman12Computational Systems Biology ILVComputational Systems Biology ILVLector: Mag.rer.nat. David Ruckerbauer1.5SWS3ECTSLecture contentsComputer 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 biotechnologyAssessment methodsHome work and final examTeaching methodsLecture and in class exercisesLanguageGerman-English1.53
4. Semesters LectureSWSECTSMaster Thesis Supervision APMaster Thesis Supervision APLector: FH-Prof.in Mag.a Dr.in Alexandra Graf0SWS1ECTSLecture contentsMethodology for the implementation of the diploma thesis: clarification of the procedure through individual presentations of the thesisAssessment methodsAssessment of the presentationTeaching methodsPresentationsLanguageGerman01Master Thesis MTMaster Thesis MTLector: FH-Prof. DI Dr. Michael Maurer0SWS28ECTSLecture contentsThe content of this course is the writing of a diploma thesis.Assessment methodsThe „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.Teaching methodsThe 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.LanguageGerman028Master Thesis Seminar SEMaster Thesis Seminar SELector: FH-Prof.in Mag.a Dr.in Alexandra Graf1SWS1ECTSLecture contentsIn the course each student presents his/her Master thesis. Progression of the thesis and potential setbacks and problems will be discussed in the group.Assessment methodsPresentationTeaching methodsPresentation, discussionLanguageGerman11
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.Equivalent certification from abroad Equivalence is determined by international agreements, validation or in individual cases a decision by the head of the academic section.Regulation for the admission of third country citizens (PDF 223 KB)Information for applicants with non-Austrian (school) certificates (PDF 145 KB)
Application To apply you will require the following documents:Proof of identity (copy of passport or copy of identity card)In case German is not your first language: Proof of German language skills at level C1Bachelor/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 transcriptLetter of motivationCV in table formPlease 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.
Admission procedure The admission procedure consists of a written test and an interview with the admission committee.Aim The aim is to ensure places are offered to those persons who complete the multi-level admission procedure with the best results. The tests are designed to assess the skills needed for an applicant's chosen profession.Procedure The written admission test assesses the applicant's knowledge of programming, molecular biology and statistics. Applicants then undergo an admission 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 admission decision. The admission requirements must be met in all cases. Applicants are evaluated according to the following weighting system: Written admission test (60%)Admission 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 admission procedure are documented in a transparent and verifiable manner.
> FH-Prof. DI Dr. Michael Maurer Head of Degree Program Bioengineering, Bioinformatics, Biotechnological Quality Management, Bioprocess Engineering T: +43 1 606 68 77-3601michael.maurer@fh-campuswien.ac.at