Support materials biomedicine/biology master Nov/Dec 2024

25 Nov. - 6 Dec. 2024

00-445 (N33) NatFak Hauptgebäude

 

Day 1 / 25 November Monday / 9:00 - 17:00

Proteins coded in genomes and protein annotations. Homology.

You are expected to take notes during the class. Also, we will write down (paper and a pen) some exercises during the class.

Before the course starts:

Be sure that you are ready to run Python and you are familiar with the JGU Jupyter server: https://cbdm-01.zdv.uni-mainz.de/~muro/teaching/p4b/em-book/c0_set_up/c0_jgu_jupyter_notebook_server.html We will use the "Biology environment" that has been set up for this class.

We will run some Python programs, review in advance the material we learned in the bachelor studies (only chapter 2): https://cbdm-01.zdv.uni-mainz.de/~muro/teaching/p4b/em-book/c2_printing_and_manipulating_text/c2_printing_and_manipulating_text.html

See this example where the whole proteome of SAR2 can be analyzed:

EM_gzip_fasta_averageProtein_sars2.ipynb (download and rename to remove the _.txt extension)

See this example where the average aa mass can be calculated:

EM_average_aa_mass.ipynb (download and rename to remove the _.txt extension)

See this example where the real average aa mass in a whole can be calculated:

EM_average_aa_mass_proteome_students.ipynb  (download and rename to remove the _.txt extension)

Or this other example where you can create a simple phylogenetic tree:

EM_simple_phylogenetic_tree.ipynb (download and rename to remove the _.txt extension)

For more functionality or in the case the JGU Jupyter server fails we will be ready to use colab. Then, open an account in colab from Google in advance: https://colab.research.google.com/

We will probably use some AI during the class. Open an account at https://chatgpt.com/ (for free) and use it in advance. Note: do not use it the day of the class before the class starts, because you have a very limited number of queries per day.

Some useful links we will use during the class:

Day 2 / 26 November Tuesday / 9:00 - 17:00

Biostatistics/Statistical genetics.

Software required: R / RStudio Desktop

R-script: Basics_in_R_1.R (download and rename to remove the .txt extension)

Slides: biostatistics_course_2024

Exercises: excercises_biostatistics

Solutions: Solutions_Basics_in_R.R

 

Day 3 / 27 November Wednesday / 9:00 - 17:00

Pairwise alignment. Multiple sequence alignment. Phylogeny.

The very same requirements as "day 1 (25 Nov)".

Day 4 / 28 November Thursday / 9:00 - 17:00

Protein structure, representation, Protein domains, disorder.

Software required: Chimera / JalView

Slides (Andrade): lesson1_chimera_7 | lesson2_domains_11

Slides (Eric Schumbera): IDR_and_LLPS_lecture_2024_Eric_Schumbera

Day 5 / 29 November Friday / 9:00 - 17:00

Protein structure prediction, low complexity, repeats. miRNAs

Data files (Andrade; repeats): MR1_fasta

Slides (Andrade): lesson3_model3D_12_MSc | lesson4_repeats_6 | lesson5_repeatsdbs_7

Data files (Mert Cihan; miRNA): sequences_mirna.fa

Slides (Mert Cihan): mirna_2024_december

Day 6 / 2 December Monday / 9:00 - 17:00

Protein interaction networks

Software required: Cytoscape

Slides (Emily Vagiona): MSc_module_P&B_2024_Function_PPIs

Day 7 / 3 December Tuesday / 9:00 - 17:00

Programming with R (I)

Software required: R / RStudio Desktop

Tutorial (Johannes Wolter): Programming_with_R_Students

Day 8 / 4 December Wednesday / 9:00 - 17:00

RNAseq.

Slides (Federico Marini): https://seafile.rlp.net/d/aa1de6f4a9f746978989/

Dynamic modelling.

Slides (Alex Anyaegbunam): DynamicModelling_ProteinKinetics

Day 9 / 5 December Thursday / 9:00 - 17:00

Programming with R (II).

Data Mining

Exercise material (Piyush More): PMo-DataMining-Exercise

Slides (Piyush More): 01_PPT-DataMining-Biomedicine

 

Day 10 / 6 December Friday / 9:00 - 13:00

Proteomics.

Slides (Ute Distler): https://seafile.rlp.net/f/3c17c782a03446e19026/?dl=1

Slides (Stefan Tenzer): https://seafile.rlp.net/f/53a584868c3a419bb7ac/ 

Software required:

Please, install in your remote desktop and test prior to the corresponding lesson using https://apps.zdv.uni-mainz.de/. If you have problems installing any of the indicated software then email the corresponding contact person (in brackets).

R: (Programming with R; Johannes Wolter)

RStudio Desktop: (Programming with R; Johannes Wolter)

Chimera: (protein 3D representation; Miguel Andrade)

JalView: (alignment and structure representation; Miguel Andrade)

Cytoscape: (Protein networks; Katja Luck)

 

Links:

Protein Data Bank (PDB): http://www.rcsb.org/

UniProt: https://www.uniprot.org/