Search result: Catalogue data in Autumn Semester 2020

Biology Master Information
Elective Major Subject Areas
Elective Major: Ecology and Evolution
Elective Concept Courses
NumberTitleTypeECTSHoursLecturers
551-0313-00LMicrobiology (Part I)W3 credits2VW.‑D. Hardt, L. Eberl, J. Piel, M. Pilhofer
AbstractAdvanced lecture class providing a broad overview on bacterial cell structure, genetics, metabolism, symbiosis and pathogenesis.
ObjectiveThis concept class will be based on common concepts and introduce to the enormous diversity among bacteria and archaea. It will cover the current research on bacterial cell structure, genetics, metabolism, symbiosis and pathogenesis.
ContentAdvanced class covering the state of the research in bacterial cell structure, genetics, metabolism, symbiosis and pathogenesis.
Lecture notesUpdated handouts will be provided during the class.
LiteratureCurrent literature references will be provided during the lectures.
Prerequisites / NoticeEnglish
The lecture "Grundlagen der Biologie II: Mikrobiologie" is the basis for this advanced lecture.
551-0309-00LConcepts in Modern Genetics
Information for UZH students:
Enrolment to this course unit only possible at ETH. No enrolment to module BIO348 at UZH.

Please mind the ETH enrolment deadlines for UZH students: Link
W6 credits4VY. Barral, D. Bopp, A. Hajnal, O. Voinnet
AbstractConcepts of modern genetics and genomics, including principles of classical genetics; yeast genetics; gene mapping; forward and reverse genetics; structure and function of eukaryotic chromosomes; molecular mechanisms and regulation of transcription, replication, DNA-repair and recombination; analysis of developmental processes; epigenetics and RNA interference.
ObjectiveThis course focuses on the concepts of classical and modern genetics and genomics.
ContentThe topics include principles of classical genetics; yeast genetics; gene mapping; forward and reverse genetics; structure and function of eukaryotic chromosomes; molecular mechanisms and regulation of transcription, replication, DNA-repair and recombination; analysis of developmental processes; epigenetics and RNA interference.
Lecture notesScripts and additional material will be provided during the semester.
551-1299-00LIntroduction to Bioinformatics Restricted registration - show details W6 credits4GS. Sunagawa, M. Gstaiger, A. Kahles, G. Rätsch, B. Snijder, E. Vayena, C. von Mering, N. Zamboni
AbstractThis course introduces principle concepts, the state-of-the-art and methods used in some major fields of Bioinformatics. Topics include: genomics, metagenomics, network bioinformatics, and imaging. Lectures are accompanied by practical exercises that involve the use of common bioinformatic methods and basic programming.
ObjectiveThe course will provide students with theoretical background in the area of genomics, metagenomics, network bioinformatics and imaging. In addition, students will acquire basic skills in applying modern methods that are used in these sub-disciplines of Bioinformatics. Students will be able to access and analyse DNA sequence information, construct and interpret networks that emerge though interactions of e.g. genes/proteins, and extract information based on computer-assisted image data analysis. Students will also be able to assess the ethical implications of access to and generation of new and large amounts of information as they relate to the identifiability of a person and the ownership of data.
ContentEthics:
Case studies to learn about applying ethical principles in human genomics research

Genomics:
Genetic variant calling
Analysis and critical evaluation of genome wide association studies

Metagenomics:
Reconstruction of microbial genomes
Microbial community compositional analysis
Quantitative metagenomics

Network bioinformatics:
Inference of molecular networks
Use of networks for interpretation of (gen)omics data

Imaging:
High throughput single cell imaging
Image segmentation
Automatic analysis of drug effects on single cell suspension (chemotyping)
Prerequisites / NoticeCourse participants have already acquired basic programming skills in Python and R.

Students will bring and work on their own laptop computers, preferentially running the latest versions of Windows or MacOSX.
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