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 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 SemesterFinal degreeMaster of Science in Engineering (MSc)27Study places120ECTSOrganisational formpart-timeApplication period for academic year 2020/21 1st January to 15th June 2020 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. Semester 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: Lukas Janker, MSc1.5SWS3ECTSLecture 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-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 Auer2.5SWS5ECTSLecture contentsExtending 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: BiopythonAssessment 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. Both count 50/50 for the gradeTeaching methodsLecture and exercises during lecture time and at homeLanguageGerman12Basics of Algorithms VOBasics of Algorithms VO1SWS2ECTSLecture contentsIntroduction to algorithms, graph theory, basic bioinformatics algorithms for predicting sequence similarity, alignments and RNA foldingAssessment methodsWritten test, evaluation of practical tasksTeaching methodsSlides and practical tasksLanguageGerman-English12Transcriptomics and Genomics ILVTranscriptomics and Genomics ILVLector: FH-Prof.in Mag.a Dr.in Alexandra Graf3.5SWS7ECTSLecture 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 % Workshop: Hand in a short program which solved a given task 60% Lecture: Written examTeaching methods- Introductions and explanations (lecture) - Exercises using the computerLanguageGerman3.57 2. Semester LectureSWSECTS Machine Learning Methods ILV 12 Applied Programming UE 36 Selected Chapters of Bioinformatics SE 12 Database Systems ILV 1.53 Medical Analysis of Genoms VO 12 Data analysis LAB 36 Specific Statistics Practice UE 12 Structure Prediction in Biopolymeres VO 12 Systems Modelling LB 24 Master Thesis Preparation SE 0.51 3. Semester LectureSWSECTSAutomation ILVAutomation ILVLector: Dipl.-Ing. Werner Seiler3SWS6ECTSLecture contentsIntroduction to process automation. Basic concepts of measurement with significance in biotechnological processes. Fundamentals of process automation, process control, in particular, programmable logic controllers (PLCs) and field bus systems. Introduction to the fundamentals of control theory.Assessment methodsHomework Written test at the end of the lecture or oral examination (TBD)Teaching methodsLecture, design and calculation exercises with Excel and simulation programs. Home exercise.LanguageGerman36Biotechnological Seminar SEBiotechnological Seminar SELector: FH-Prof.in Mag.a Dr.in Alexandra Graf, FH-Prof. DI Dr. Michael Maurer0.5SWS1ECTSLecture 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, WorkshopLanguageGerman24Good Clinical Practice and Pharmacovigilance VOGood Clinical Practice and Pharmacovigilance VOLector: Stefan Smyczko, MSc1SWS2ECTSLecture contentsUPDATE LECTURE TITLE: 2SOFTWARE 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 Clinical Data and EthicsAssessment 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 / Presentations1.53Metagenom 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.12Molecular 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, MSc BSc1SWS2ECTSLecture 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. 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: Dr. Jürgen Zanghellini1.5SWS3ECTSLecture 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. Semester LectureSWSECTS Master Thesis Supervision MT 11 Master Thesis MT 028 Master Thesis Seminar SE 11Semester datesSummer semester 2020: 10th February to 12th July 2020Winter semester 2020/21: 17th August 2020 to 31st January 2021 Number of teaching weeks20 per semester Times6.00 p.m.-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 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 creditsWith 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 abroadRegulation for the admission of third country citizensInformation for applicants with non-Austrian (school) certificatesEquivalence 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 abroadCertificates 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. Admission procedure The admission procedure consists of a written test and an interview with the admission committee.AimThe 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.ProcedureThe 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.CriteriaThe 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. Studying with disabilities You want to apply for the course and require support due to a disability, chronic illness or restriction?Please contact:Mag.a Ursula WeilenmannGender & Diversity Management barrierefrei@fh-campuswien.ac.at 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. Teaching staff and research staff > FH-Prof.in Mag.a Dr.in Alexandra Graf 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 Downloads and Links Information Folder Bioinformatics Master (PDF)Folder Applied Life Sciences (PDF)
1. Semester 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: Lukas Janker, MSc1.5SWS3ECTSLecture 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-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 Auer2.5SWS5ECTSLecture contentsExtending 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: BiopythonAssessment 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. Both count 50/50 for the gradeTeaching methodsLecture and exercises during lecture time and at homeLanguageGerman12Basics of Algorithms VOBasics of Algorithms VO1SWS2ECTSLecture contentsIntroduction to algorithms, graph theory, basic bioinformatics algorithms for predicting sequence similarity, alignments and RNA foldingAssessment methodsWritten test, evaluation of practical tasksTeaching methodsSlides and practical tasksLanguageGerman-English12Transcriptomics and Genomics ILVTranscriptomics and Genomics ILVLector: FH-Prof.in Mag.a Dr.in Alexandra Graf3.5SWS7ECTSLecture 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 % Workshop: Hand in a short program which solved a given task 60% Lecture: Written examTeaching methods- Introductions and explanations (lecture) - Exercises using the computerLanguageGerman3.57
2. Semester LectureSWSECTS Machine Learning Methods ILV 12 Applied Programming UE 36 Selected Chapters of Bioinformatics SE 12 Database Systems ILV 1.53 Medical Analysis of Genoms VO 12 Data analysis LAB 36 Specific Statistics Practice UE 12 Structure Prediction in Biopolymeres VO 12 Systems Modelling LB 24 Master Thesis Preparation SE 0.51
3. Semester LectureSWSECTSAutomation ILVAutomation ILVLector: Dipl.-Ing. Werner Seiler3SWS6ECTSLecture contentsIntroduction to process automation. Basic concepts of measurement with significance in biotechnological processes. Fundamentals of process automation, process control, in particular, programmable logic controllers (PLCs) and field bus systems. Introduction to the fundamentals of control theory.Assessment methodsHomework Written test at the end of the lecture or oral examination (TBD)Teaching methodsLecture, design and calculation exercises with Excel and simulation programs. Home exercise.LanguageGerman36Biotechnological Seminar SEBiotechnological Seminar SELector: FH-Prof.in Mag.a Dr.in Alexandra Graf, FH-Prof. DI Dr. Michael Maurer0.5SWS1ECTSLecture 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, WorkshopLanguageGerman24Good Clinical Practice and Pharmacovigilance VOGood Clinical Practice and Pharmacovigilance VOLector: Stefan Smyczko, MSc1SWS2ECTSLecture contentsUPDATE LECTURE TITLE: 2SOFTWARE 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 Clinical Data and EthicsAssessment 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 / Presentations1.53Metagenom 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.12Molecular 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, MSc BSc1SWS2ECTSLecture 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. 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: Dr. Jürgen Zanghellini1.5SWS3ECTSLecture 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. Semester LectureSWSECTS Master Thesis Supervision MT 11 Master Thesis MT 028 Master Thesis Seminar SE 11
> 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