Lecture Notes:

PDF, opens an external URL in a new window (3.6 MB, 2017-04-06)
PDF, opens an external URL in a new window (optimized version, 2.3 MB, 2017-04-06)

Slides:

• Part 1 (PDF), opens an external URL in a new window (2.8 MB)
• Part 2 (PDF), opens an external URL in a new window (5.7 MB)
• Part 3 (PDF), opens an external URL in a new window (2 MB)
• Part 4 (PDF), opens an external URL in a new window (2 MB)

Videos presented during the class:

• Proteins and Amino Acids, opens an external URL in a new window
• DNA Replication, opens an external URL in a new window
• Protein Synthesis, opens an external URL in a new window
• Protein 3D Structure, opens an external URL in a new window
• Ribosome, opens an external URL in a new window
• DNA transcription, Promoter, opens an external URL in a new window
• DNA transcription, Activator, Repressor, opens an external URL in a new window
• DNA, opens an external URL in a new window
• tRNA, opens an external URL in a new window
• Cell surface, opens an external URL in a new window
• Pathway, Cell, Insulin, opens an external URL in a new window
• Pathway, Cell, Hormone, opens an external URL in a new window
• Nanomachine / Protein, opens an external URL in a new window
• Nanomachine/ Protein, opens an external URL in a new window
• Pathway, Glycolysis, opens an external URL in a new window

Motivation:

Life sciences will dominate the 21st century: As soon as we understand the complex functional network of the cell we can develop cures for most diseases. Nanomachines will have a strong impact on the industry of the future. We are still far from a complete understanding of this network, but bioinformatics is undoubtedly the key technology to get there. Bioinformatics played an integral role in one of mankind's most notable advances - the complete sequencing of the human genome. However, despite this scientific quantum leap rendered possible by bioinformatics, we are just at the beginning of deciphering life as the genomic sequence alone tells us nothing about structure or function of the encoded proteins. Moreover the interpretation of the genetic code depends on the state of the cell as the approximately 30,000 genes of the human genome account for about 300,000 different proteins. The mechanisms that control gene activation, its scale and timing in order for the appropriate proteins to be synthesized are not yet well understood.

One of the primary tasks in bioinformatics is to help analyze genomic data.Bioinformatics approaches are also needed to interpret, analyse, compare, manage and simulate data collected by molecular biological measurement techniques such as x-ray crystallography, magnetic resonance spectroscopy, mass spectroscopy, atomic force spectroscopy, fluorescence spectroscopy, as well as microarray and protein array techniques. One of the long-term objectives in bioinformatics is to replace molecular biological experiments by simulations and predictions made in silico as this would mean immense cost savings and accelerate the development of novel nanotechnologies and drugs.

No prior biological knowledge is necessary for this course. It starts off with an introduction to bioinformatics methods, covers the basics of molecular cell biology and then proceeds to important molecular biological data bases and algorithms. The ideas and concepts behind algorithms are explained and results mathematically interpreted.

Topics:

• Introduction to molecular biology of the cell
• Bioinformatics software
• Biological databases (genomes and proteins, 3D-structures, domains, protein classes, motifs, publications)
• Sequence comparison (global and local alignments, gap penalties, similarity measures like PAM and BLOSUM, alignment statistics, algorithms like BLAST, FASTA and BLAT)
• Multiple sequence comparison
• Phylogenies (exact and approximative methods)