Course Contents
• 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)
Preconditions
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)
Preconditions
Recommended is „General Computer Science I“
- Lehrende: Heinz Köppl
- Lehrende: Yujie Zhong
Semester: Inverno 2023/24