Search result: Catalogue data in Autumn Semester 2018

Biotechnology Master Information
Core Courses
Students need to acquire a total of 8 ECTS in lectures in this category.
The list of core courses is a closed list, no other course can be added to this category.
Students need to pass both lectures offered in this category.
NumberTitleTypeECTSHoursLecturers
636-0101-00LSystems Genomics
Does not take place this semester.
This lecture will take place again in Spring Semester 2019.
O4 credits3GN. Beerenwinkel, S. Reddy
AbstractThis lecture course is an introduction to Systems Genomics. It addresses how fundamental questions in biological systems are studied and how the resulting data is statistically analyzed in order to derive predictive mathematical models. The focus is on viewing biology from a genomic perspective, which requires high-throughput experimental methods (e.g., RNA-seq, genome-scale screening, single-cell
ObjectiveThe goal of this course is to learn how a detailed quantitative description of genome biology can be employed for a better understanding of molecular and cellular processes and function. Students will learn fundamental questions driving the field of Systems Genomics. They will also be introduced to traditional and advanced state-of-the-art technologies (e.g., CRISPR-Cas9 screening, droplet-microfluidic sequencing, cellular genetic barcoding) that are used to obtain quantitative data in Systems Genomics. They will learn how to use these data to develop mathematical models and efficient statistical inference algorithms to recognize patterns, molecular interrelationships, and systems behavior. Finally, students will gain a perspective of how Systems Genomics can be used for applied biological sciences (e.g., drug discovery and screening, bio-production, cell line engineering, biomarker discovery, and diagnostics).
ContentLectures in Systems Genomics will alternate between lectures on (i) biological questions, experimental technologies, and applications, and (ii) statistical data analysis and mathematical modeling. Selected complex biological systems and the respective experimental tools for a quantitative analysis will be presented. Some specific examples are the use of RNA-sequencing to do quantitative gene expression profiling, CRISPR-Cas9 genome scale screening to identify genes responsible for drug resistance, single-cell measurements to identify novel cellular phenotypes, and genetic barcoding of cells to dissect development and lineage differentiation.

Main Topics:
-- Next-generation sequencing
-- Transcriptomics
-- Biological network analysis
-- Functional and perturbation genomics
-- Single-cell biology and analysis
-- Genomic profiling of the immune system
-- Genomic profiling of cancer
-- Evolutionary genomics
-- Genome-wide association studies

Selected genomics datasets will be analyzed by students in the tutorials using the statistical programming language R and dedicated Bioconductor packages.
Lecture notesThe PowerPoint presentations of the lectures as well as other course material relevant for an active participation will be made available online.
Literature-- Do K-A, Qin ZS & Vannucci M (2013) Advances in Statistical Bioinformatics: Models and Integrative Inference for High-Throughput Data, Cambridge University Press
-- Klipp E. et al (2009) Systems Biology, Wiley-Blackwell
-- Alon U (2007) An Introduction to Systems Biology, Chapman & Hall
-- Zvelebil M & Baum JO (2008) Understanding Bioinformatics, Garland Science
636-0102-00LAdvanced BioengineeringO4 credits3SS. Panke, Y. Benenson, P. S. Dittrich, M. Fussenegger, A. Hierlemann, M. H. Khammash, D. J. Müller, R. Paro, R. Platt, T. Schroeder
AbstractThis course provides an overview of modern concepts of bioengineering across different levels of complexity, from single molecules to systems, microscaled reactors to production environments, and across different fields of applications
ObjectiveStudents will be able to recognize major developments in bioengineering across different organisms and levels of complexity and be able to relate it to major technological and conceptual advances in the underlying sciences.
ContentMolecular and cellular engineering; Synthetic biology: Engineering strategies in biology; from single molecules to systems; downscaling bioengineering; Bioengineering in chemistry, pharmaceutical sciences, and diagnostics, personalized medicine.
Lecture notesHandouts during class
LiteratureWill be announced during the course
Practical Training
Students need to acquire a total of 14 ECTS in lab courses.
All listed lab courses are mandatory.
NumberTitleTypeECTSHoursLecturers
636-0201-00LLab Course: Methods in Cell Analysis and Laboratory Automation Restricted registration - show details
Only for Biotechnology MSc, Programme Regulations 2017.
O2 credits6PT. Horn
AbstractThe course Methods in Cell Analysis and Laboratory Automation introduces students to high-end cell analysis and sample preparation methods including image analysis. Students will be taught theoretical aspects and skills in Flow Cytometry, Light Microscopy, Image Analysis, and the use of Laboratory Automation.
Objective-to understand the technical and physical principles of light microscopes and flow cytometers
-to have hands-on experience in the use of these technologies to analyze/image real samples
-to be able to run a basic analysis of the data and images obtained with flow cytometers and microscopes
-to get introduced to liquid handling (pipetting) robotics and learn how to implement a basic workflow
ContentThe practical course will have five units at 2 days each (total 10 days):
1. Flow Cytometry:
a. Introduction to Flow Cytometry
b. Practical demonstration on flow cytometry analyzers and flow cytometry cell sorters
c. Flow cytometry sample preparation
d. Learn how to use flow cytometry equipment to analyze and sort fluorescence-labeled cells
2. Light microscopy
a. Learn how to build a microscope and understand the underlying physical principles
b. Learn how to use a modern automated wide field fluorescence microscope
c. Use this microscope to automatically acquire images of a cell culture assay to analyze the dose-dependent effect of a drug treatment
3. Image Analysis
a. Introduction to the fundamentals of image analysis
b. Learn the basics of the image analysis software Fiji/ImageJ
c. Use Fiji/ImageJ to analyze the images acquired during the microscopy exercise
4. Laboratory Automation
a. Introduction to the basics of automated liquid handling/ lab robotics
b. See examples on using lab automation for plasmid library generation and cell cultivation
c. Learn how to program and execute a basic pipetting workflow including liquid handling and labware transfers on Tecan and Hamilton robotic systems
5. Presentations
a. Each student will be assigned to an individual topic of the course and will have to prepare a presentation on it.
b. Presentations and discussion in form of a Colloquium
Lecture notesYou will find further information on the practical course and the equipment at:
Link
Link
LiteratureMicroscopy: Murphy and Davidson, Fundamentals of Light Microscopy and Electronic Imaging, John Wiley & Sons, 2012
Flow Cytometry: Shapiro, Practical Flow Cytometry, John Wiley & Sons, 2005
Image analysis: R. C. Gonzalez, R. E. Woods, Digital Image Processing (3rd Edition), Prentice Hall
Laboratory Automation: Design and construction of a first-generation high-throughput integrated robotic molecular biology platform for bioenergy applications (2011) J. Lab. Autom., 16(4), 292-307
Prerequisites / NoticeThe following knowledge is required for the course:
-basic laboratory methods
-basic physics of optics (properties of light, refraction, lenses, fluorescence)
-basic biology of cells (cell anatomy and physiology)
636-0202-00LLab Course: Next-Generation Sequencing Restricted registration - show details
Does not take place this semester.
Only for Biotechnology MSc, Programme Regulations 2017.

Attention: this lab course will be offered again in Spring semester 2019.
O2 credits5PR. Paro, S. Reddy
AbstractThe Lab Course will take place Monday/Tuesday 9-17h, 10 days in total, start of this lab course is on Monday, September 25 2017.
ObjectiveStudents shall obtain a basic understanding in NGS and its application in transcription profiling including theoretical considerations when starting an RNA-seq experiment and the practical hands-on work of library preparation and usage of bioinformatics tools for data analysis.
ContentIntroduction to NGS technologies and applications. Design of an RNA-seq transcription profiling experiment. Specific treatment of cells (+/- signal-induction) and RNA extraction. Handling and quality control of RNA samples. Sequencing library preparation starting with total RNA. Quality control and quantification of the libraries. Setup of an NGS run and sequencing of the prepared RNA-seq libraries using the NextSeq 500 system. Analysis of the generated sequence data: sequence data QC, criteria for run performance and quality of data; pre-processing of the raw data; mapping sequence reads to a reference sequence; quantification of transcript abundance and differential gene expression.
Lecture notesMaterial will be provided during the course
LiteratureSara Goodwin, John D. McPherson & W. Richard McCombie. Coming of age: ten years of next-generation sequencing technologies. Nature Reviews Genetics 17, 333-351 (2016)

Zhong Wang, Mark Gerstein & Michael Snyder. RNA-Seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics 10, 57-63 (January 2009)

Fatih Ozsolak & Patrice M. Milos. RNA sequencing: advances, challenges and opportunities. Nature Reviews Genetics 12, 87-98 (February 2011)

Ana Conesa, Pedro Madrigal, Sonia Tarazona et al. A survey of best practices for RNA-seq data analysis. Genome Biology 2016 17:13.
636-0203-00LLab Course: Microsystems and Microfluidics in Biology Restricted registration - show details
Only for Biotechnology MSc, Programme Regulations 2017.
O2 credits5PP. S. Dittrich, A. Hierlemann
AbstractThis practical course is an introduction to microsystems technology and microfluidics for the life sciences. It includes basic concepts of microsystem design, fabrication, and assembly into an experimental setup. Biological applications include a variety of measurements of cellular and tissue signals and subsequent analysis.
ObjectiveThe students are introduced to the basic principles of microsystems technology. They get acquainted with practical scientific work and learn the entire workflow of (a) understanding the theoretical concept, (b) planning the experiment, (c) engineering of the needed device, (d) execution of the experiment and data acquisition, (e) data evaluation and analysis, and (f) reporting and discussion of the results.
ContentThe practical course will consist of a set of 4 experiments.
Lecture notesNotes and guidelines will be provided at the beginning of the course.
Literature- S.M. Sze, "Semiconductor Devices, Physics and Technology", 2nd edition, Wiley, 2002
- W. Menz, J. Mohr, O. Paul, "Microsystem Technology", Wiley-VCH, 2001
- G. T. A. Kovacs, "Micromachined Transducers Sourcebook", McGraw-Hill, 1998
- M. J. Madou, "Fundamentals of Microfabrication", 2nd ed., CRC Press, 2002
- N.-T. Nguyen and S. Wereley, "Fundamentals and Applications of Microfluidics", Artech House, ISBN 1-580-53343-4
- O. Geschke et al., "Microsystem Engineering for Chemistry and the Life Sciences", Wiley-VCH, ISBN 3-527-30733-8
Prerequisites / NoticeThe practical course will consist of a set of 4 experiments. For each experiment, the student will be required to
- understand the theoretical concept behind the experiment
- plan the experiment
- engineer the devices
- execute the experiments and acquire data
- evaluate and analyze the data
- report and discuss the results
A good quality of the final report will be expected and be an important criterion.
636-0204-00LLab Course: Microbial Biotechnology Restricted registration - show details
Only for Biotechnology MSc, Programme Regulations 2017.
O2 credits5PM. Held
AbstractStudents will learn the foundations of monoseptic working practice and create and screen microbial libraries for identification of strains expressing different fluorescent protein (XFP) levels
ObjectiveStudents will learn the foundations of monoseptic working practice and create and screen microbial libraries for identification of strains expressing different fluorescent protein (XFP) levels
ContentBlock A: Handling and preparation and of microbial libraries
D1: Introduction to microbiological cultures and monoseptic working techniques.
D2: Plasmid-based expression systems and variation of XFP synthesis levels via site-directed RBS mutagenesis.
Block B: Library screening
D3: In vivo screening for XFP expression levels.
D4: Analysis of XFP levels via SDS-PAGE analysis. RBS-sequencing.
Block C: Hit recovery and validation
D5: In silico analysis of RBS variants.
D6: Cellular XFP content for selected variants at different culture conditions.
Block D: Data analysis and presentation
D7: Protein expression analysis. Q&A for reports and presentations.
D8: Final presentations and wrap-up.
Lecture notesMaterial will be provided during the course.
Literature(1) Reetz MT, Kahakeaw D, and Lohmer R. "Addressing the numbers problem in directed evolution." ChemBioChem 2008
(2) Jeschek M, Gerngross D, and Panke S. “Rationally reduced libraries for combinatorial pathway optimization minimizing experimental effort.” Nat. Commun. 2016
(3) Salis HM. “The ribosome binding site calculator.” Methods Enzymol. 2011
(4) Nienhaus G, Nienhaus K, and Wiedenmann J. "Structure–Function Relationships in Fluorescent Marker Proteins of the Green Fluorescent Protein Family." Fluorescent Proteins I. Springer Berlin Heidelberg, 2011

General introduction to microbiology:

(5) Schlegel HG, and Zaborosch C. “General Microbiology.” Cambridge University Press 1993
(6) Pirt JS. “Principles of microbe and cell cultivation.” Blackwell Scientific Publications 1975
Advanced Courses
Students need to aquire a total of 24 ECTS in this category.
The list of advanced courses is a closed list, no other course can be added to this category.
Biomelecular-Orientated
NumberTitleTypeECTSHoursLecturers
636-0103-00LMicrotechnology
Attention: This course was offered in previous semesters with the number: 636-0020-00 "Microtechnology and Microelectronics". Students that already passed course 636-0020-00 cannot receive credits for course 636-0103-00.
W4 credits3GA. Hierlemann
AbstractStudents are introduced to the basics of microtechnology, cleanroom, semiconductor and silicon process technologies. They will get to know the fabrication of mostly silicon-based microdevices and -systems and all related microfabrication processes.
ObjectiveStudents are introduced to the basics of microtechnology, cleanroom, semiconductor and silicon process technologies. They will get to know the different fabrication methods for various microdevices and systems.
ContentIntroduction to microtechnology, semiconductors, and micro electro mechanical systems (MEMS)

- Fundamentals of semiconductors and band model
- Fundamentals of devices: transistor and diode.
- Silicon processing and fabrication steps
- Silicon crystal structure and manufacturing
- Thermal oxidation
- Doping via diffusion and ion implantation
- Photolithography
- Thin film deposition: dielectrics and metals
- Wet etching & bulk micromachining
- Dry etching & surface micromachining
- Microtechnological processing and fabrication sequence
- Optional: Packaging
Lecture notesHandouts in English
Literature- S.M. Sze, "Semiconductor Devices, Physics and Technology", 2nd edition, Wiley, 2002
- R.F. Pierret, "Semiconductor Device Fundamentals", Addison Wesley, 1996
- R. C. Jaeger, "Introduction to Microelectronic Fabrication", Prentice Hall 2002
- S.A. Campbell, "The Science and Engineering of Microelectronic Fabrication", 2nd edition, Oxford University Press, 2001
- W. Menz, J. Mohr, O. Paul, "Microsystem Technology", Wiley-VCH, 2001
- G. T. A. Kovacs, "Micromachined Transducers Sourcebook", McGraw-Hill, 1998
- M. J. Madou, "Fundamentals of Microfabrication", 2nd ed., CRC Press, 2002
Prerequisites / NoticeFundamentals in physics and physicochemistry (orbital models etc.) are required, a repetitorium of fundamental physics and quantum theory at the semester beginning can be offered.

The information on the web can be updated until the beginning of the semester.
636-0104-00LBiophysical Methods
Attention: This course was offered in previous semesters with the number: 626-0010-00L "Nanomachines of the Cell (Part I): Principles". Students that already passed course 626-0010-00 cannot receive credits for course 636-0104-00.
W4 credits3GD. J. Müller
AbstractStudents will be imparted knowledge in basic and advanced biophysical methods applied to problems in molecular biotechnology. The course is fundamental to applying the methods in their daily and advanced research routines. The students will learn the physical basis of the methods as well as their limitations and possibilities to address existing and future topics in molecular biotechnology.
ObjectiveGain of interdisciplinary competence in experimental and theoretical research, which qualifies for academic scientific work (master's or doctoral thesis) as well as for research in a biotechnology or a pharmaceutical company. The module is of general use in courses focused on modern biomolecular technologies, systems biology and systems engineering.
ContentThe students will learn basic and advanced knowledge in applying biophysical methods to address problems and overcome challenges in biotechnology, cell biology and life sciences in general. The biological and physical possibilities and limitations of the methods will be discussed and critically evaluated. By the end of the course the students will have assimilated knowledge on a portfolio of biophysical tools widening their research capabilities and aptitude.
The biophysical methods to be taught will include:
• Light microscopy: Resolution limit of light microscopy, fluorescence, GFP, fluorescence microscopy, DIC, phase contrast, difference between wide-field and confocal microscopy
• Super resolution optical microscopy: STED, PALM, STORM, other variations
• Electron microscopy: Scanning electron microscopy, transmission electron microscopy, electron tomography, cryo-electron microscopy, single particle analysis and averaging, tomography, sectioning, negative stain
• X-ray, electron and neutron diffraction
• MRI Imaging
• Scanning tunnelling microscopy and atomic force microscopy
• Patch clamp technologies: Principles of patch clamp analysis and application. Various patch clamp approaches used in research and industry
• Surface plasmon resonance-based biosensors
• Molecular pore-based sensors and sequencing devices
• Mechanical molecular and cellular assembly devices
• Optical and magnetic tweezers
• CD spectroscopy
• Optogenetics
• Molecular dynamics simulations
Lecture notesHand out will be given to students at lecture.
LiteratureMethods in Molecular Biophysics (5th edition), Serdyuk et al., Cambridge University Press
Biochemistry (5th edition), Berg, Tymoczko, Stryer; ISBN 0-7167-4684-0, Freeman
Bioanalytics, Lottspeich & Engels, Wiley VCH, ISBN-10: 3527339191
Cell Biology, Pollard & Earnshaw; ISBN:0-7216-3997-6, Saunder, Pennsylvania
Methods in Modern Biophysics, Nölting, 3rd Edition, Springer, ISBN-10: 3642030211
Prerequisites / NoticeThe module is composed of 3 SWS (3 hours/week): 2-hour lecture, 1-hour seminar. For the seminar, students will prepare oral presentations on specific in-depth subjects with/under the guidance of the teacher.
636-0105-00LIntroduction to Biological Computers
Attention: This course was offered in previous semesters with the number: 636-0011-00L "Introduction to Biological Computers". Students that already passed course 636-0011-00L cannot receive credits for course 636-0105-00L.
W4 credits3GY. Benenson
AbstractBiological computers are man-made biological networks that interrogate and control cells and organisms in which they operate. Their key features, inspired by computer science, are programmability, modularity, and versatility. The course will show how to rationally design, implement and test biological computers using molecular engineering, DNA nanothechnology and synthetic biology.
ObjectiveThe course has the following objectives:

* Familiarize students with parallels between theories in computer science and engineering and information-processing in live cells and organisms

* Introduce basic theories of computation

* Introduce approaches to creating novel biological computing systems in non-living environment and in living cells including bacteria, yeast and mammalian/human cells.

The covered approaches will include
- Nucleic acids engineering
- DNA and RNA nanotechnology
- Synthetic biology and gene circuit engineering
- High-throughput genome engineering and gene circuit assembly

* Equip the students with computer-aided design (CAD) tools for biocomputing circuit engineering. A number of tutorials will introduce MATLAB SimBiology toolbox for circuit design and simulations

* Foster creativity, research and communication skills through semester-long "Design challenge" assignment in the broad field of biological computing and biological circuit engineering.
ContentNote: the exact subjects can change, the details below should only serve for general orientation

Lecture 1. Introduction: what is molecular computation (part I)?

* What is computing in general?
* What is computing in the biological context (examples from development, chemotaxis and gene regulation)
* The difference between natural computing and engineered biocomputing systems

Lecture 2: What is molecular computation (part II) + State machines

1st hour

* Detailed definition of an engineered biocomputing system
* Basics of characterization
* Design challenge presentation

2nd hour

* Theories of computation: state machines (finite automata and Turing machines)

Lecture 3: Additional models of computation

* Logic circuits
* Analog circuits
* RAM machines

Basic approaches to computer science notions relevant to molecular computation. (i) State machines; (ii) Boolean networks; (iii) analog computing; (iv) distributed computing. Design Challenge presentation.

Lecture 4. Classical DNA computing

* Adleman experiment
* Maximal clique problem
* SAT problem

Lecture 5: Molecular State machines through self-assembly

* Tiling implementation of state machine
* DNA-based tiling system
* DNA/RNA origami as a spin-off of self-assembling state machines

Lecture 6: Molecular State machines that use DNA-encoded tapes

* Early theoretical work
* Tape extension system
* DNA and enzyme-based finite automata for diagnostic applications

Lecture 7: Introduction to cell-based logic and analog circuits

* Computing with (bio)chemical reaction networks
* Tuning computation with ultrasensitivity and cooperativity
* Specific examples

Lecture 8: Transcriptional circuits I

* Introducing transcription-based circuits
* General features and considerations
* Guidelines for large circuit construction

Lecture 9: Transcriptional circuits II

* Large-scale distributed logic circuits in bacteria
* Toward large-scale circuits in mammalian cells

Lecture 10: RNA circuits I

* General principles of RNA-centered circuit design
* Riboswitches and sRNA regulation in bacteria
* Riboswitches in yeast and mammalian cells
* General approach to RNAi-based computing

Lecture 11: RNA circuits II

* RNAi logic circuits
* RNAi-based cell type classifiers
* Hybrid transcriptional/posttranscriptional approaches

Lecture 12: In vitro DNA-based logic circuits

* DNAzyme circuits playing tic-tac-toe against human opponents
* DNA brain


Lecture 13: Advanced topics

* Engineered cellular memory
* Counting and sequential logic
* The role of evolution
* Fail-safe design principles

Lecture 14: Design challenge presentation
Lecture notesLecture notes will be available online
LiteratureAs a way of general introduction, the following two review papers could be useful:

Benenson, Y. RNA-based computation in live cells. Current Opinion in Biotechnology 2009, 20:471:478

Benenson, Y. Biocomputers: from test tubes to live cells. Molecular Biosystems 2009, 5:675:685

Benenson, Y. Biomolecular computing systems: principles, progress and potential (Review). Nature Reviews Genetics 13, 445-468 (2012).
Prerequisites / NoticeBasic knowledge of molecular biology is assumed.
636-0108-00LBiological Engineering and Biotechnology
Attention: This course was offered in previous semesters with the number: 636-0003-00L "Biological Engineering and Biotechnology". Students that already passed course 636-0003-00L cannot receive credits for course 636-0108-00L.
W4 credits3VM. Fussenegger
AbstractBiological Engineering and Biotechnology will cover the latest biotechnological advances as well as their industrial implementation to engineer mammalian cells for use in human therapy. This lecture will provide forefront insights into key scientific aspects and the main points in industrial decision-making to bring a therapeutic from target to market.
ObjectiveBiological Engineering and Biotechnology will cover the latest biotechnological advances as well as their industrial implementation to engineer mammalian cells for use in human therapy. This lecture will provide forefront insights into key scientific aspects and the main points in industrial decision-making to bring a therapeutic from target to market.
Content1. Insight Into The Mammalian Cell Cycle. Cycling, The Balance Between Proliferation and Cancer - Implications For Biopharmaceutical Manufacturing. 2. The Licence To Kill. Apoptosis Regulatory Networks - Engineering of Survival Pathways To Increase Robustness of Production Cell Lines. 3. Everything Under Control I. Regulated Transgene Expression in Mammalian Cells - Facts and Future. 4. Secretion Engineering. The Traffic Jam getting out of the Cell. 5. From Target To Market. An Antibody's Journey From Cell Culture to The Clinics. 6. Biology and Malign Applications. Do Life Sciences Enable the Development of Biological Weapons? 7. Functional Food. Enjoy your Meal! 8. Industrial Genomics. Getting a Systems View on Nutrition and Health - An Industrial Perspective. 9. IP Management - Food Technology. Protecting Your Knowledge For Business. 10. Biopharmaceutical Manufacturing I. Introduction to Process Development. 11. Biopharmaceutical Manufacturing II. Up- stream Development. 12. Biopharmaceutical Manufacturing III. Downstream Development. 13. Biopharmaceutical Manufacturing IV. Pharma Development.
Lecture notesHandout during the course.
636-0107-00LMicrobial BiotechnologyW4 credits3GS. Panke, M. Jeschek
AbstractStudents of this course know and can evaluate modern methods of microbial biotechnology and enzyme technology and understand their relation to modern applications of microbial biotechnology.
ObjectiveStudents of this course know and can evaluate modern methods of microbial biotechnology and enzyme technology and understand their relation to modern applications of microbial biotechnology.
ContentThe course will cover in its main part selected fundamental and advanced topics and methodologies in microbial molecular biotechnology. Major topics include I) Microbial physiology of microbes (prokaryotes and selected fungi), II) Applications of Microbial Biotechnology, III) Enzymes - advanced kinetics and engineering, IV) Principles of in vivo directed evolution, V) System approaches to cell engineering/metabolic engineering, and VI) Trends in Microbial Biotechnology. The course is a mix of lectures and different exercise formats.
Lecture notesNotes will be provided in the forms of handouts.
LiteratureThe course will use selected parts of textbooks and then original scientific publications and reviews.
636-0018-00LData Mining IW6 credits3G + 2AK. M. Borgwardt
AbstractData Mining, the search for statistical dependencies in large databases, is of utmost important in modern society, in particular in biological and medical research. This course provides an introduction to the key problems, concepts, and algorithms in data mining, and the applications of data mining in computational biology.
ObjectiveThe goal of this course is that the participants gain an understanding of data mining problems and algorithms to solve these problems, in particular in biological and medical applications.
ContentThe goal of the field of data mining is to find patterns and statistical dependencies in large databases, to gain an understanding of the underlying system from which the data were obtained. In computational biology, data mining contributes to the analysis of vast experimental data generated by high-throughput technologies, and thereby enables the generation of new hypotheses.

In this course, we will present the algorithmic foundations of data mining and its applications in computational biology. The course will feature an introduction to popular data mining problems and algorithms, reaching from classification via clustering to feature selection. This course is intended for both students who are interested in applying data mining algorithms and students who would like to gain an understanding of the key algorithmic concepts in data mining.

Tentative list of topics:

1. Distance functions
2. Classification
3. Clustering
4. Feature Selection
Lecture notesCourse material will be provided in form of slides.
LiteratureWill be provided during the course.
Prerequisites / NoticeBasic understanding of mathematics, as taught in basic mathematics courses at the Bachelor's level.
636-0550-00LBiomolecular NanotechnologyW3 credits2VM. Nash
AbstractBiomolecular nanotechnology is a broad field that focuses on the study and science of biological materials including DNA, RNA and proteins at length scales below 10 nm. This is a broad overview of the topic with a focus on current research themes.
ObjectiveThe objective is to familiarise the students with a broad range of topics related to biotechnology, nanotechnology, and biophysics with a focus on current research and reading of scientific literature.
ContentIntroduction to biomacromolecules; Measurement techniques for characterisation of biomacromolecules; Fundamentals of molecular recognition; Recombinant DNA; Protein engineering; Directed evolution; Protein folding; Polymers; Elastin-like polypeptides; Intelligent materials; Spatially localized hydrogels; Mechanical properties of proteins and macromolecules; Single-molecule force spectroscopy
LiteratureRepresentative literature:
(1) Alberts, Molecular Biology (Ch.2 Cellular chemistry).
(2) Ratner, Biomaterials Science (Ch. 2.3, 2.4 Polymers & hydrogels).
(3) Walsh, Protein Biochemistry, (Ch. 2, Protein Structure).
(4) Nath et. al. Analytical chemistry, 74(3): 504-509, 2002.
(5) DeMonte, D., et. al. Proteins DOI: 10.1002/prot.24320, 2013.
(6) Feldhaus, M.J., et al. Nature Biotechnology 21 (2): 163–70, 2003.
(7) Link, A.J., et al. PNAS 103 (27): 10180–85, 2006.
(8) Chen, I. et al. PNAS 108 (28): 11399–404, 2011.
(9) Marín-Navarro, J., et. al. PloS One 10 (12). journals.plos.org: e0144289, 2015.
(10) Christensen, T. et al. Biomacromolecules 14 (5): 1514–19, 2013.
(11) Shimoboji, T., et al. PNAS. 99(26): 16592-16596, 2002.
(12) Puchner, E.M. et al. PNAS. 105(36): 13385–13390, 2008.
(13) Dietz, H., et al. PNAS 103 (5): 1244–47, 2006.
636-0117-00LMathematical Modelling for Bioengineering and Systems Biology Information W4 credits3GD. Iber
AbstractBasic concepts and mathematical tools to explore biochemical reaction kinetics and biological network dynamics.
ObjectiveThe course enables students to formulate, analyse, and simulate mathematical models of biochemical networks. To this end, the course covers basic mathematical concepts and tools to explore biochemical reaction dynamics as well as basic concepts from dynamical systems theory. The exercises serve to deepen the understanding of the presented concepts and the mathematical methods, and to train students to numerically solve and simulate mathematical models.
ContentBiochemical Reaction Modelling
Basic Concepts from Linear Algebra & Differential Equations Mathematical Methods: Linear Stability Analysis, Phase Plane Analysis, Bifurcation Analysis Dynamical Systems: Switches, Oscillators, Adaptation Signal Propagation in Signalling Networks Parameter Estimation
636-0118-00LIntroduction to Dynamical Systems with Applications to BiologyW4 credits3GM. H. Khammash, A. Gupta
AbstractMany physical systems are dynamic and are characterized by internal variables that change with time. Describing the quantitative and qualitative features of this change is the topic of dynamical systems theory. Dynamical systems arise naturally in virtually all scientific disciplines including physics, biology, chemistry and engineering. This course is a broad introduction to the topic dynamical s
ObjectiveThe goal of this course is to introduce the student to dynamical systems and to develop a solid understanding of their fundamental properties. The theory will be developed systematically, focusing on analytical methods for low dimensional systems, geometric intuition, and application examples from biology. Computer simulations using matlab will be used to demonstrate various concepts
ContentA dynamical view of the world; the importance of nonlinearity; solutions of differential equations; solving equations on the computer; the phase plane; fixed points and stability; linear stability analysis; classifications of linear systems; Liapunov functions and nonlinear stability; cycles and oscillations; bifurcations and bifurcation diagrams. Many biological examples will be used through the course to demonstrate the concepts
Lecture notesWill be provided as needed.
LiteratureStrogatz, S. H. (2018). Nonlinear dynamics and chaos: with applications to physics, biology, chemistry, and engineering. CRC Press.

Segel, L. A., & Edelstein-Keshet, L. (2013). A Primer in Mathematical Models in Biology (Vol. 129). SIAM.
Prerequisites / NoticePrerequisites: Calculus; a first course in differential equations; basic linear algebra (eigenvalues and eigenvectors). Matlab programming.
System-Orientated
NumberTitleTypeECTSHoursLecturers
636-0103-00LMicrotechnology
Attention: This course was offered in previous semesters with the number: 636-0020-00 "Microtechnology and Microelectronics". Students that already passed course 636-0020-00 cannot receive credits for course 636-0103-00.
W4 credits3GA. Hierlemann
AbstractStudents are introduced to the basics of microtechnology, cleanroom, semiconductor and silicon process technologies. They will get to know the fabrication of mostly silicon-based microdevices and -systems and all related microfabrication processes.
ObjectiveStudents are introduced to the basics of microtechnology, cleanroom, semiconductor and silicon process technologies. They will get to know the different fabrication methods for various microdevices and systems.
ContentIntroduction to microtechnology, semiconductors, and micro electro mechanical systems (MEMS)

- Fundamentals of semiconductors and band model
- Fundamentals of devices: transistor and diode.
- Silicon processing and fabrication steps
- Silicon crystal structure and manufacturing
- Thermal oxidation
- Doping via diffusion and ion implantation
- Photolithography
- Thin film deposition: dielectrics and metals
- Wet etching & bulk micromachining
- Dry etching & surface micromachining
- Microtechnological processing and fabrication sequence
- Optional: Packaging
Lecture notesHandouts in English
Literature- S.M. Sze, "Semiconductor Devices, Physics and Technology", 2nd edition, Wiley, 2002
- R.F. Pierret, "Semiconductor Device Fundamentals", Addison Wesley, 1996
- R. C. Jaeger, "Introduction to Microelectronic Fabrication", Prentice Hall 2002
- S.A. Campbell, "The Science and Engineering of Microelectronic Fabrication", 2nd edition, Oxford University Press, 2001
- W. Menz, J. Mohr, O. Paul, "Microsystem Technology", Wiley-VCH, 2001
- G. T. A. Kovacs, "Micromachined Transducers Sourcebook", McGraw-Hill, 1998
- M. J. Madou, "Fundamentals of Microfabrication", 2nd ed., CRC Press, 2002
Prerequisites / NoticeFundamentals in physics and physicochemistry (orbital models etc.) are required, a repetitorium of fundamental physics and quantum theory at the semester beginning can be offered.

The information on the web can be updated until the beginning of the semester.
636-0104-00LBiophysical Methods
Attention: This course was offered in previous semesters with the number: 626-0010-00L "Nanomachines of the Cell (Part I): Principles". Students that already passed course 626-0010-00 cannot receive credits for course 636-0104-00.
W4 credits3GD. J. Müller
AbstractStudents will be imparted knowledge in basic and advanced biophysical methods applied to problems in molecular biotechnology. The course is fundamental to applying the methods in their daily and advanced research routines. The students will learn the physical basis of the methods as well as their limitations and possibilities to address existing and future topics in molecular biotechnology.
ObjectiveGain of interdisciplinary competence in experimental and theoretical research, which qualifies for academic scientific work (master's or doctoral thesis) as well as for research in a biotechnology or a pharmaceutical company. The module is of general use in courses focused on modern biomolecular technologies, systems biology and systems engineering.
ContentThe students will learn basic and advanced knowledge in applying biophysical methods to address problems and overcome challenges in biotechnology, cell biology and life sciences in general. The biological and physical possibilities and limitations of the methods will be discussed and critically evaluated. By the end of the course the students will have assimilated knowledge on a portfolio of biophysical tools widening their research capabilities and aptitude.
The biophysical methods to be taught will include:
• Light microscopy: Resolution limit of light microscopy, fluorescence, GFP, fluorescence microscopy, DIC, phase contrast, difference between wide-field and confocal microscopy
• Super resolution optical microscopy: STED, PALM, STORM, other variations
• Electron microscopy: Scanning electron microscopy, transmission electron microscopy, electron tomography, cryo-electron microscopy, single particle analysis and averaging, tomography, sectioning, negative stain
• X-ray, electron and neutron diffraction
• MRI Imaging
• Scanning tunnelling microscopy and atomic force microscopy
• Patch clamp technologies: Principles of patch clamp analysis and application. Various patch clamp approaches used in research and industry
• Surface plasmon resonance-based biosensors
• Molecular pore-based sensors and sequencing devices
• Mechanical molecular and cellular assembly devices
• Optical and magnetic tweezers
• CD spectroscopy
• Optogenetics
• Molecular dynamics simulations
Lecture notesHand out will be given to students at lecture.
LiteratureMethods in Molecular Biophysics (5th edition), Serdyuk et al., Cambridge University Press
Biochemistry (5th edition), Berg, Tymoczko, Stryer; ISBN 0-7167-4684-0, Freeman
Bioanalytics, Lottspeich & Engels, Wiley VCH, ISBN-10: 3527339191
Cell Biology, Pollard & Earnshaw; ISBN:0-7216-3997-6, Saunder, Pennsylvania
Methods in Modern Biophysics, Nölting, 3rd Edition, Springer, ISBN-10: 3642030211
Prerequisites / NoticeThe module is composed of 3 SWS (3 hours/week): 2-hour lecture, 1-hour seminar. For the seminar, students will prepare oral presentations on specific in-depth subjects with/under the guidance of the teacher.
636-0105-00LIntroduction to Biological Computers
Attention: This course was offered in previous semesters with the number: 636-0011-00L "Introduction to Biological Computers". Students that already passed course 636-0011-00L cannot receive credits for course 636-0105-00L.
W4 credits3GY. Benenson
AbstractBiological computers are man-made biological networks that interrogate and control cells and organisms in which they operate. Their key features, inspired by computer science, are programmability, modularity, and versatility. The course will show how to rationally design, implement and test biological computers using molecular engineering, DNA nanothechnology and synthetic biology.
ObjectiveThe course has the following objectives:

* Familiarize students with parallels between theories in computer science and engineering and information-processing in live cells and organisms

* Introduce basic theories of computation

* Introduce approaches to creating novel biological computing systems in non-living environment and in living cells including bacteria, yeast and mammalian/human cells.

The covered approaches will include
- Nucleic acids engineering
- DNA and RNA nanotechnology
- Synthetic biology and gene circuit engineering
- High-throughput genome engineering and gene circuit assembly

* Equip the students with computer-aided design (CAD) tools for biocomputing circuit engineering. A number of tutorials will introduce MATLAB SimBiology toolbox for circuit design and simulations

* Foster creativity, research and communication skills through semester-long "Design challenge" assignment in the broad field of biological computing and biological circuit engineering.
ContentNote: the exact subjects can change, the details below should only serve for general orientation

Lecture 1. Introduction: what is molecular computation (part I)?

* What is computing in general?
* What is computing in the biological context (examples from development, chemotaxis and gene regulation)
* The difference between natural computing and engineered biocomputing systems

Lecture 2: What is molecular computation (part II) + State machines

1st hour

* Detailed definition of an engineered biocomputing system
* Basics of characterization
* Design challenge presentation

2nd hour

* Theories of computation: state machines (finite automata and Turing machines)

Lecture 3: Additional models of computation

* Logic circuits
* Analog circuits
* RAM machines

Basic approaches to computer science notions relevant to molecular computation. (i) State machines; (ii) Boolean networks; (iii) analog computing; (iv) distributed computing. Design Challenge presentation.

Lecture 4. Classical DNA computing

* Adleman experiment
* Maximal clique problem
* SAT problem

Lecture 5: Molecular State machines through self-assembly

* Tiling implementation of state machine
* DNA-based tiling system
* DNA/RNA origami as a spin-off of self-assembling state machines

Lecture 6: Molecular State machines that use DNA-encoded tapes

* Early theoretical work
* Tape extension system
* DNA and enzyme-based finite automata for diagnostic applications

Lecture 7: Introduction to cell-based logic and analog circuits

* Computing with (bio)chemical reaction networks
* Tuning computation with ultrasensitivity and cooperativity
* Specific examples

Lecture 8: Transcriptional circuits I

* Introducing transcription-based circuits
* General features and considerations
* Guidelines for large circuit construction

Lecture 9: Transcriptional circuits II

* Large-scale distributed logic circuits in bacteria
* Toward large-scale circuits in mammalian cells

Lecture 10: RNA circuits I

* General principles of RNA-centered circuit design
* Riboswitches and sRNA regulation in bacteria
* Riboswitches in yeast and mammalian cells
* General approach to RNAi-based computing

Lecture 11: RNA circuits II

* RNAi logic circuits
* RNAi-based cell type classifiers
* Hybrid transcriptional/posttranscriptional approaches

Lecture 12: In vitro DNA-based logic circuits

* DNAzyme circuits playing tic-tac-toe against human opponents
* DNA brain


Lecture 13: Advanced topics

* Engineered cellular memory
* Counting and sequential logic
* The role of evolution
* Fail-safe design principles

Lecture 14: Design challenge presentation
Lecture notesLecture notes will be available online
LiteratureAs a way of general introduction, the following two review papers could be useful:

Benenson, Y. RNA-based computation in live cells. Current Opinion in Biotechnology 2009, 20:471:478

Benenson, Y. Biocomputers: from test tubes to live cells. Molecular Biosystems 2009, 5:675:685

Benenson, Y. Biomolecular computing systems: principles, progress and potential (Review). Nature Reviews Genetics 13, 445-468 (2012).
Prerequisites / NoticeBasic knowledge of molecular biology is assumed.
636-0108-00LBiological Engineering and Biotechnology
Attention: This course was offered in previous semesters with the number: 636-0003-00L "Biological Engineering and Biotechnology". Students that already passed course 636-0003-00L cannot receive credits for course 636-0108-00L.
W4 credits3VM. Fussenegger
AbstractBiological Engineering and Biotechnology will cover the latest biotechnological advances as well as their industrial implementation to engineer mammalian cells for use in human therapy. This lecture will provide forefront insights into key scientific aspects and the main points in industrial decision-making to bring a therapeutic from target to market.
ObjectiveBiological Engineering and Biotechnology will cover the latest biotechnological advances as well as their industrial implementation to engineer mammalian cells for use in human therapy. This lecture will provide forefront insights into key scientific aspects and the main points in industrial decision-making to bring a therapeutic from target to market.
Content1. Insight Into The Mammalian Cell Cycle. Cycling, The Balance Between Proliferation and Cancer - Implications For Biopharmaceutical Manufacturing. 2. The Licence To Kill. Apoptosis Regulatory Networks - Engineering of Survival Pathways To Increase Robustness of Production Cell Lines. 3. Everything Under Control I. Regulated Transgene Expression in Mammalian Cells - Facts and Future. 4. Secretion Engineering. The Traffic Jam getting out of the Cell. 5. From Target To Market. An Antibody's Journey From Cell Culture to The Clinics. 6. Biology and Malign Applications. Do Life Sciences Enable the Development of Biological Weapons? 7. Functional Food. Enjoy your Meal! 8. Industrial Genomics. Getting a Systems View on Nutrition and Health - An Industrial Perspective. 9. IP Management - Food Technology. Protecting Your Knowledge For Business. 10. Biopharmaceutical Manufacturing I. Introduction to Process Development. 11. Biopharmaceutical Manufacturing II. Up- stream Development. 12. Biopharmaceutical Manufacturing III. Downstream Development. 13. Biopharmaceutical Manufacturing IV. Pharma Development.
Lecture notesHandout during the course.
636-0018-00LData Mining IW6 credits3G + 2AK. M. Borgwardt
AbstractData Mining, the search for statistical dependencies in large databases, is of utmost important in modern society, in particular in biological and medical research. This course provides an introduction to the key problems, concepts, and algorithms in data mining, and the applications of data mining in computational biology.
ObjectiveThe goal of this course is that the participants gain an understanding of data mining problems and algorithms to solve these problems, in particular in biological and medical applications.
ContentThe goal of the field of data mining is to find patterns and statistical dependencies in large databases, to gain an understanding of the underlying system from which the data were obtained. In computational biology, data mining contributes to the analysis of vast experimental data generated by high-throughput technologies, and thereby enables the generation of new hypotheses.

In this course, we will present the algorithmic foundations of data mining and its applications in computational biology. The course will feature an introduction to popular data mining problems and algorithms, reaching from classification via clustering to feature selection. This course is intended for both students who are interested in applying data mining algorithms and students who would like to gain an understanding of the key algorithmic concepts in data mining.

Tentative list of topics:

1. Distance functions
2. Classification
3. Clustering
4. Feature Selection
Lecture notesCourse material will be provided in form of slides.
LiteratureWill be provided during the course.
Prerequisites / NoticeBasic understanding of mathematics, as taught in basic mathematics courses at the Bachelor's level.
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