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choderalab / assaytools

Modeling and Bayesian analysis of fluorescence and absorbance assays.
http://assaytools.readthedocs.org
GNU Lesser General Public License v2.1
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Determine depency of delG error on dPstated #106

Open sonyahanson opened 7 years ago

sonyahanson commented 7 years ago

Tested the effect of changing dPstated = 0.35 * inputs['Pstated'] to dPstated = 0.15 * inputs['Pstated']. Interestingly, this removed the long tails for the Src-Erlotonib fits, changing them from this (dPstated = 0.35 * inputs['Pstated']):

src-erlotinib-ef_binding_iter0

to this (dPstated = 0.15 * inputs['Pstated']):

src-erlotinib-ef_binding_iter0

Similarly for the same number of iterations, running the same job three times gives more consistent answers with dPstated at 0.15, changing this (dPstated = 0.35 * inputs['Pstated']):

comparing_src_geferl_3iter

to this (dPstated = 0.15 * inputs['Pstated']): comparing_src_geferl_3iter

MehtapIsik commented 7 years ago

This is very interesting!

dPstate =0.15 can still be a realistic number. I wonder what would happen if you make uncertainty in protein concentration absurdly low. Something like dPstate =0.01 or 0.001. I wonder if fitting the model will get more difficult or will DeltaG uncertainties get narrower and narrower making the model look better (perhaps wrongly).