Difference between revisions of "Module 2: How well does sequence similarity predict similarity in binding specificity?"
Line 5: | Line 5: | ||
* Key claim of the paper: "Similarity in sequence of binding motifs of PDZ domains can be used to identify 16 distinct specificity classes." | * Key claim of the paper: "Similarity in sequence of binding motifs of PDZ domains can be used to identify 16 distinct specificity classes." | ||
− | * Data and | + | * Data and Instructions |
+ | |||
+ | **Download all the raw data needed for this course at: xxx | ||
+ | **Try opening the LOLA software (see instruction in README.txt). | ||
+ | **Make sure R is installed in your computer | ||
+ | **Make sure you have Java | ||
* Schedule: | * Schedule: | ||
**H1: General intro to the paper/motivation | **H1: General intro to the paper/motivation | ||
− | **H2-3: Write code to import the data and | + | **H2-3: Write code to import the data and compute the Position Weight Matrics |
**H4-6: Write code to compute and compare different types of similarity values and do the clustering. | **H4-6: Write code to compute and compare different types of similarity values and do the clustering. | ||
− | **H7: Use | + | **H7: Use the LOLA visualization software to look at the data. |
**H8: Start writing the report | **H8: Start writing the report | ||
**H9: Broader view on the use and challenges with similarity metrics between biological objects | **H9: Broader view on the use and challenges with similarity metrics between biological objects |
Revision as of 16:07, 15 October 2015
- Title: "How well does sequence similarity predict similarity in binding specificity?"
- Paper to be examined: “A Specificity Map for the PDZ Domain Family”, PLoS Biol 6(9): e239 [1]
- Key claim of the paper: "Similarity in sequence of binding motifs of PDZ domains can be used to identify 16 distinct specificity classes."
- Data and Instructions
- Download all the raw data needed for this course at: xxx
- Try opening the LOLA software (see instruction in README.txt).
- Make sure R is installed in your computer
- Make sure you have Java
- Schedule:
- H1: General intro to the paper/motivation
- H2-3: Write code to import the data and compute the Position Weight Matrics
- H4-6: Write code to compute and compare different types of similarity values and do the clustering.
- H7: Use the LOLA visualization software to look at the data.
- H8: Start writing the report
- H9: Broader view on the use and challenges with similarity metrics between biological objects
- Key bioinformatics concept of this module:
- Similarity measures between biological objects (here protein sequence and binding specificity)
- Clustering