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-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 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 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. Semester 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: 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: DI Dr. Albert Kriegner, DI(FH) Dr. Stephan Pabinger1SWS2ECTSLecture 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 studentsTeaching methods- lecture with exercise - presentations done 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 MSc2SWS4ECTSLecture contentsOxford Nanopore data will be analysed by chosen appropriate methods and establishing an analysis pipeline. In the wet lab DNA will be extracted and sequenced. The created data will be analysed with the method that was established with the literature data.Assessment methodsImmanent examination, (protocol and results of analysis)Teaching methodsPresentation, practical 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 Heiderer3SWS6ECTSLecture contentsThis 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 codeAssessment methodsSmall self-written program at end of courseTeaching methodsPresentations and discussions, hands-on practice on the PC, discussions.LanguageGerman-English36Applied Programming Practice ILVApplied Programming Practice ILVLector: Ing. Christian Binder, BSc, Msc Josef Moser, 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. Semester LectureSWSECTSAutomation ILVAutomation ILVLector: Daniel Mitterecker, BSc, MSc, Smriti Shridhar, PhD3SWS6ECTSLecture contentsIntroduction 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.Assessment methodsHomework Written test at the end of the lecture.Teaching methodsLecture, example exercises. Home exercises to practice learned concepts.LanguageEnglish36Biotechnological 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, 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 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 / 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. 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. Semester LectureSWSECTS Master Thesis Supervision AP 01 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