Yaakov Benenson: Catalogue data in Autumn Semester 2020 |
| Name | Dr. Yaakov Benenson |
| Department | Biosystems Science and Engineering |
| Relationship | Associate Professor |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 636-0102-00L | Advanced Bioengineering | 4 credits | 3S | S. Panke, Y. Benenson, P. S. Dittrich, M. Fussenegger, A. Hierlemann, M. H. Khammash, A. Moor, D. J. Müller, M. Nash, R. Platt, J. Stelling, B. Treutlein | |
| Abstract | This 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 | ||||
| Learning objective | Students 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. | ||||
| Content | Molecular 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 notes | Handouts during class | ||||
| Literature | Will be announced during the course | ||||
| 636-0105-00L | Introduction 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. | 4 credits | 3G | Y. Benenson | |
| Abstract | Biological 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. | ||||
| Learning objective | The 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. | ||||
| Content | Note: 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 notes | Lecture notes will be available online | ||||
| Literature | As 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 / Notice | Basic knowledge of molecular biology is assumed. | ||||
| 636-0301-00L | Current Topics in Biosystems Science and Engineering For doctoral students only. Master's students cannot receive credits for the seminar. | 2 credits | 1S | R. Platt, N. Beerenwinkel, Y. Benenson, K. M. Borgwardt, P. S. Dittrich, M. Fussenegger, A. Hierlemann, D. Iber, M. H. Khammash, A. Moor, D. J. Müller, S. Panke, S. Reddy, T. Schroeder, T. Stadler, J. Stelling, B. Treutlein | |
| Abstract | This seminar will feature invited lectures about recent advances and developments in systems biology, including topics from biology, bioengineering, and computational biology. | ||||
| Learning objective | To provide an overview of current systems biology research. | ||||
| Content | The final list of topics will be available at https://www.bsse.ethz.ch/news-and-events/seminar-series.html | ||||
| 636-0507-00L | Synthetic Biology II  Does not take place this semester. Students in the MSc Programme Biotechnology may select Synthetic Biology II instead of the Research Project 1. | 8 credits | 4A | S. Panke, Y. Benenson, J. Stelling | |
| Abstract | 7 months biological design project, during which the students are required to give presentations on advanced topics in synthetic biology (specifically genetic circuit design) and then select their own biological system to design. The system is subsequently modeled, analyzed, and experimentally implemented. Results are presented at an international student competition at the MIT (Cambridge). | ||||
| Learning objective | The students are supposed to acquire a deep understanding of the process of biological design including model representation of a biological system, its thorough analysis, and the subsequent experimental implementation of the system and the related problems. | ||||
| Content | Presentations on advanced synthetic biology topics (eg genetic circuit design, adaptation of systems dynamics, analytical concepts, large scale de novo DNA synthesis), project selection, modeling of selected biological system, design space exploration, sensitivity analysis, conversion into DNA sequence, (DNA synthesis external,) implementation and analysis of design, summary of results in form of scientific presentation and poster, presentation of results at the iGEM international student competition (www.igem.org). | ||||
| Lecture notes | Handouts during course | ||||
| Prerequisites / Notice | The final presentation of the project is typically at the MIT (Cambridge, US). Other competing schools include regularly Imperial College, Cambridge University, Harvard University, UC Berkeley, Princeton Universtiy, CalTech, etc. This project takes place between end of Spring Semester and beginning of Autumn Semester. Registration in April. Please note that the number of ECTS credits and the actual work load are disconnected. | ||||