From 2 November 2020, the autumn semester 2020 will take place online. Exceptions: Courses that can only be carried out with on-site presence. Please note the information provided by the lecturers via e-mail.

Sai Reddy: Catalogue data in Autumn Semester 2018

Name Prof. Dr. Sai Reddy
FieldSystems and Synthetic Immunology
Address
Systems and Synthetic Immunology
ETH Zürich, D-BSSE, BSD H 324
Mattenstrasse 26
4058 Basel
SWITZERLAND
Award: The Golden Owl
Telephone+41 61 387 33 68
E-mailsai.reddy@bsse.ethz.ch
DepartmentBiosystems Science and Engineering
RelationshipAssociate Professor

NumberTitleECTSHoursLecturers
636-0101-00LSystems Genomics
Does not take place this semester.
This lecture will take place again in Spring Semester 2019.
4 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
636-0202-00LLab 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.
2 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.
636-0301-00LCurrent Topics in Biosystems Science and Engineering
For doctoral students only.
Master's students cannot receive credits for the seminar.
2 credits1SR. Platt, N. Beerenwinkel, Y. Benenson, K. M. Borgwardt, P. S. Dittrich, M. Fussenegger, A. Hierlemann, D. Iber, M. H. Khammash, D. J. Müller, S. Panke, R. Paro, S. Reddy, T. Schroeder, T. Stadler, J. Stelling
AbstractThis seminar will feature invited lectures about recent advances and developments in systems biology, including topics from biology, bioengineering, and computational biology.
ObjectiveTo provide an overview of current systems biology research.
ContentThe final list of topics will be available at https://www.bsse.ethz.ch/news-and-events/seminar-series.html