Hubert Pausch: Catalogue data in Spring Semester 2018 |
Name | Prof. Dr. Hubert Pausch |
Field | Animal Genomics |
Address | Professur für Tiergenomik ETH Zürich, LFW B 58.2 Universitätstrasse 2 8092 Zürich SWITZERLAND |
Telephone | +41 44 633 66 81 |
hubert.pausch@usys.ethz.ch | |
URL | http://www.ag.ethz.ch |
Department | Environmental Systems Science |
Relationship | Associate Professor |
Number | Title | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|
751-6003-00L | Training Course in Research Groups (Large) | 6 credits | 13P | M. Kreuzer, R. Mandel, E. Mandel, S. Neuenschwander, H. Pausch, S. E. Ulbrich | |
Abstract | The students will learn the conceptual and methodological background of research in the animal science groups of the Institute of Plant, Animal and Agroecosystem Science. In addition to teaching the theoretical background, the major aim of the course is to integrate the students into the research groups (on job training) and, hence, to focus on the practical application of the knowledge. | ||||
Learning objective | - Introduction into the conceptual and methodological basis of research - Integration of the students into the research groups (on job training) - Application of the gained knowledge | ||||
Content | The students will be integrated into the research groups’ day-to-day work and will thus deal with all aspects of scientific work. This comprises the planning (conceptually and logistically), execution (data collection, laboratory analyses) and evaluation (statistics, data presentation) of experiments as well as the basics of scientific writing (aim: later publication, Master thesis). The research topics and the range of methodologies vary between the animal science research groups of the Institute of Plant, Animal and Agroecosystem Sciences. | ||||
Lecture notes | None | ||||
Literature | Specific readings after enlisting in a particular research group. | ||||
Prerequisites / Notice | The number of training slots in the various groups is limited. It is therefore highly recommended to contact the group leaders early enough (first come first serve). The full integration in a research group often means to work on weekends. The total time budget is equivalent to about 180 hours. Active participation in group meetings (discussion, presentation) and short written reports about the work conducted are required for the 6 credit points. There are no grades, it is only pass or fail. | ||||
751-6003-01L | Training Course in Research Groups (Small) | 3 credits | 6P | M. Kreuzer, R. Mandel, E. Mandel, S. Neuenschwander, H. Pausch, S. E. Ulbrich | |
Abstract | The students will learn the conceptual and methodological background of research in the animal science groups of the Institute of Plant, Animal and Agroecosystem Science. In addition to teaching the theoretical background, the major aim of the course is to integrate the students into the research groups (on job training) and, hence, to focus on the practical application of the knowledge. | ||||
Learning objective | - Introduction into the conceptual and methodological basis of research - Integration of the students into the research groups (on job training) - Application of the gained knowledge | ||||
Content | The students will be integrated into the research groups’ day-to-day work and will thus deal with all aspects of scientific work. This comprises the planning (conceptually and logistically), execution (data collection, laboratory analyses) and evaluation (statistics, data presentation) of experiments as well as the basics of scientific writing (aim: later publication, Master thesis). The research topics and the range of methodologies vary between the animal science research groups of the Institute of Plant, Animal and Agroecosystem Sciences. | ||||
Lecture notes | None | ||||
Literature | Specific readings after enlisting in a particular research group. | ||||
Prerequisites / Notice | The number of training slots in the various groups is limited. It is therefore highly recommended to contact the group leaders early enough (first come first serve). The full integration in a research group often means to work on weekends. The total time budget is equivalent to about 90 hours. Active participation in group meetings (discussion, presentation) and short written reports about the work conducted are required for the 3 credit points. There are no grades, it is only pass or fail. | ||||
751-6244-00L | Genomic Animal Breeding | 3 credits | 3G | H. Pausch | |
Abstract | Molecular marker-based methods and applications in animal breeding and genetics are introduced by discussing approaches to discover genomic regions associated with monogenic and complex traits, genomic prediction as well as the properties of genomic breeding values. Participants analyse real genomic data with the R-package and thus acquire the skills to carry out own research projects. | ||||
Learning objective | After the course, students will be able to - work with widely-used formats of genomic data - process and interpret raw sequencing and genotyping data - explain and identify the challenges, opportunities and risks associated with applying molecular marker data in animal breeding and animal genetics - apply common statistical methods to correlate phenotypes and genotypes - carry out research projects that involve molecular marker data | ||||
Content | - Principles of generating, processing and analysing whole-genome sequencing and genotyping data - Bioinformatics approaches to characterize sequence variation at nucleotide level - Statistical approaches to map quantitative trait loci using genome-wide association studies - Calculation of genomic relationship and inbreeding coefficients - Principles of genomic prediction and selection - Approaches to identify causal mutations underlying Mendelian traits - Strategies to consider Mendelian traits in genomic breeding programs - Identification of differentially expressed genes using genome-wide transcriptomics data - Principles of genome editing and possible applications in livestock breeding programs | ||||
Lecture notes | The slides will be provided in advance of each lecture. | ||||
Prerequisites / Notice | Laptop with the R software for exercises Basic experience with the R environment for statistical computing (a brief introduction into R will be provided upon request) |