Bioinformatics and Evolutionary Genomics
The sequencing revolution is rapidly charting ever more obscure branches in the tree of life. All these novel genomes and increasingly sophisticated bioinformatic methods are changing our view of where the complexity in our protein complexes come from and how the genes in the human genome came from. For example when we trace compare the
Algorithms in Bioinformatics
Modern biology routinely generates huge amounts of data: sequences, from NGS experiments; quantitative data, from -omics experiments; and graphs, representing molecular interactions. At the heart of many bioinformatics applications are algorithms that handle such types of data in time- and memory-efficient ways. Almost invariably these algorithms optimize some criterion – e.g. alignment quality, energy function
Data Analysis for Plant and Animal Breeding
Data analysis is central to both plant and animal breeding, and the size and complexity of phenotypic and genomic data sets continue to increase. Thus, the ability to analyze and interpret such large data sets is an essential skill for breeders, both in science and industry. In this course you will become familiar with state-of-the-art
Fundamentals of Genetics
the Genetic and Molecular Biological Approach to Biology; single-gene inheritance; independent assortment of genes; mapping eukaryote chromosomes by recombination; gene interaction; transcription, processing and translation of RNA in Eukaryotes; regulation of eukaryotic gene expression; genomes and genomics; large-scale chromosomal changes; gene isolation and manipulation; population genetics; inheritance of complex traits.
Bioinformatics and Dynamic Modelling
This course introduces students to the research fields of bioinformatics and biological modeling. Central themes are the use of data to extract underlying patterns on function and evolution, and the use of models to test hypotheses and make predictions for biological systems. Introduction: Biological processes are notoriously complex, and studying their dynamics through modeling and
Applied Machine Learning
Machine learning is marking a revolution in the world. From an academic research topic, over the last decade it has shift to a major paradigm used in many companies for a wide range of services. From deleting SPAM mail from your inbox to ranking the Google search results, and from defining your Facebook stream to
Perspectives on Information and Society
The main aim of the course is to critically reflect on concepts central to Information Studies in terms of assumptions, limitations, and social and ethical implications. As information is the central notion of Information Studies we start with information. We approach information by using hermeneutics; this perspective highlights the characteristics of human understanding and is
Philosophy of A.I. (UU)
This course will make students familiar with fundamental issues in the philosophy of AI, and will introduce them to several current discussions in the field. Students will practice their argumentation and presentation skills, both in class discussions and in writing. The course is split up in three parts. The first part is a quick overview
Population and Quantitative Genetics
Life on earth shows immense variation, both in phenotypes and the underlying genotypes. Population and quantitative geneticists address questions such as where this variation comes from, how it is maintained, and how it can be used. This course introduces seminal models and concepts that deal with the dynamics of genetic variation, and applies these to