Lehrinhalte
Biomolecular foundations of high-throughput measurement techniques
(Microarrays, RNA-Seq, genome sequencing, proteinarrays, mass-spectrometry, flow-cytometry, mass-cytometry, genomics, proteomics, metabolomics)
Foundations of statistics and machine learning (decision theory, regression, classification and clustering)
Exact substring search, dynamic programming, algorithms for sequence comparison (PAM, BLAST, BLAST2, etc), alignment of multiple sequences (ClustalW, DAlign, etc)
Important databases in bioinformatics and their use in medicine and biology (GenBank, Gene Expression Omnibus, Rfam, UniProt, Pfam, KEGG, BRENDA, Pathway Commons)
Analysis of interaction networks (modularity, graph partitioning, spanning trees, differential network analysis, network motifs, STRING database, PathBLAST)
Introduction to structural biology, structure prediction for RNA and proteins, Protein Data Bank (PDB)
Voraussetzungen
Recommended is General Computer Science I
Biomolecular foundations of high-throughput measurement techniques
(Microarrays, RNA-Seq, genome sequencing, proteinarrays, mass-spectrometry, flow-cytometry, mass-cytometry, genomics, proteomics, metabolomics)
Foundations of statistics and machine learning (decision theory, regression, classification and clustering)
Exact substring search, dynamic programming, algorithms for sequence comparison (PAM, BLAST, BLAST2, etc), alignment of multiple sequences (ClustalW, DAlign, etc)
Important databases in bioinformatics and their use in medicine and biology (GenBank, Gene Expression Omnibus, Rfam, UniProt, Pfam, KEGG, BRENDA, Pathway Commons)
Analysis of interaction networks (modularity, graph partitioning, spanning trees, differential network analysis, network motifs, STRING database, PathBLAST)
Introduction to structural biology, structure prediction for RNA and proteins, Protein Data Bank (PDB)
Voraussetzungen
Recommended is General Computer Science I
- Lehrende: Philipp Fröhlich
- Lehrende: Heinz Köppl
- Lehrende: Yujie Zhong
Semester: WT 2021/22