1. What were my goals for this week?
- Look at heuristic algorithms to cluster motions more quickly/intelligently
- See if I can optimize the hierarchical clustering further
- Try other forms of clustering on the motions
- Figure out what to do with k-means outliers
- Implement affine fitting on the clusters
- Talk to Aaron about glyphs for static representation of motions!
2. What did I accomplish this week?
- Spoke to Aaron about glyphs - he suggested clustering by alpha carbons to speed up process
- Implemented coarse kmeans using alpha carbon motions only
- Implemented coarse hierarchy using residues
- Implemented list version of coarse hierarchy - takes all candidates and deals with them at once
- Did some time trials on the versions of hierarchical clustering
- Thoroughly documented above code for future use
- Implemented hierarchical clustering that takes bonding information and motion
3. Why are numbers 1 and 2 different?
Determined with Mike that affine fitting could be done by someone else, while I should concentrate on the portions of the code that I know well. Aaron was sick most of the week, so no further progress could be made on glyphs.
4. What are my goals for next week?
- Get ready for the semester to begin!
5. How does this fit in my bigger picture?
My bigger picture: got a good idea of how graduate research works, got my feet wet, learned a lot. The lab's bigger picture: got commented clustering code for future use on the motion representation project.
6. What did I read this week?
- Zavodszky, Maria I. et al, Modeling Correlated Main-Chain Motions in Proteins for Flexible Molecular Recognition.
- Thorpe, M.F. et al, Protein Flexibility and Dynamics Using Constraint Theory.
- Lei, Ming et al, Sampling Protein Conformations and Pathways.
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