9:50 A – 8:30 P
Goals
- Write SDB abstract.
- OligoPaint prep
* Run probe design
* Order probes
3. Chromatin color region selection
* write script to chose genomic regions based on size, color, and color-confidence score.
Genomics
Probe Design
- GenerateProbeSequences.m – Generates orthogonal N-mers to a whole list of specifications.
- Generated local BLAST libraries for Drosophila, Ecoli, and our combined current probes & primers.
- Sent FASTA files and BLAST reports for probes to Jeff.
- Ordered probes
Mathematical Modeling as Markov processes
- Discussed derivation of necessary and sufficient conditions for a chemical system to have MM-type kinetics.
- Observations:
- Models used carelessly can produce inappropriate biological conclusions: example: inferring k_d and a simple MM enzyme-substrate biochemical relations because the data are well described by the simple MM model — this is not the only model which fits that data.
- While you can rarely say “this is the correct model” based on your data, you can say something about the class of models consistent with the data and the class of models inconsistent with the data, given the proper model tools. — Markov processes are a great way of organizing and comparing model classes.
- Quantitative data (e.g. kinetic data) may tell you things about your model structure you might not have realized are there — like the minimum number of states in your system.
- see email discussion