Suchergebnis: Katalogdaten im Herbstsemester 2018

Biotechnologie Master Information
Vertiefungsfächer
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.
System-Orientierung
NummerTitelTypECTSUmfangDozierende
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 KP3GA. Hierlemann
KurzbeschreibungStudents 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.
LernzielStudents 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.
InhaltIntroduction 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
SkriptHandouts in English
Literatur- 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
Voraussetzungen / BesonderesFundamentals 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 KP3GD. J. Müller
KurzbeschreibungStudents 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.
LernzielGain 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.
InhaltThe 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
SkriptHand out will be given to students at lecture.
LiteraturMethods 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
Voraussetzungen / BesonderesThe 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 KP3GY. Benenson
KurzbeschreibungBiological 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.
LernzielThe 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.
InhaltNote: 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
SkriptLecture notes will be available online
LiteraturAs 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).
Voraussetzungen / BesonderesBasic 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 KP3VM. Fussenegger
KurzbeschreibungBiological 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.
LernzielBiological 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.
Inhalt1. 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.
SkriptHandout during the course.
636-0018-00LData Mining IW6 KP3G + 2AK. M. Borgwardt
KurzbeschreibungData 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.
LernzielThe 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.
InhaltThe 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
SkriptCourse material will be provided in form of slides.
LiteraturWill be provided during the course.
Voraussetzungen / BesonderesBasic understanding of mathematics, as taught in basic mathematics courses at the Bachelor's level.
636-0117-00LMathematical Modelling for Bioengineering and Systems Biology Information W4 KP3GD. Iber
KurzbeschreibungBasic concepts and mathematical tools to explore biochemical reaction kinetics and biological network dynamics.
LernzielThe 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.
InhaltBiochemical 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 KP3GM. H. Khammash, A. Gupta
KurzbeschreibungMany 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
LernzielThe 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
InhaltA 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
SkriptWill be provided as needed.
LiteraturStrogatz, 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.
Voraussetzungen / BesonderesPrerequisites: Calculus; a first course in differential equations; basic linear algebra (eigenvalues and eigenvectors). Matlab programming.
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