Rocky Mountains Conference EPR Workshop DEER Analysis programs

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Rocky Mountains Conference EPR Workshop: DEER Analysis programs testing

Rocky Mountains Conference EPR Workshop: DEER Analysis programs testing

DEFit (for CW spectra: Cwdip. Fit) Sen I. , Logan, T. and Fajer P.

DEFit (for CW spectra: Cwdip. Fit) Sen I. , Logan, T. and Fajer P. , Biochemistry, 2007; 46: 11639 -49. http: //fajerpc. magnet. fsu. edu/Programs/DEFit/defit. html

 • All spectra were provided by the anonymous symposium participants and analyzed blindly

• All spectra were provided by the anonymous symposium participants and analyzed blindly using DEFit (till today we don’t know what the spectra are) • The spectrum naming (slide titles) follow the key provided by the panel moderator, Dr. Eric Hustedt. • Hardware: Intel Duo Core 2, Matlab 2007 b

2 a 3 Gaussians C A, B • components A and B very well

2 a 3 Gaussians C A, B • components A and B very well defined: narrow distributions assymetric population • component (c) badly defined component

2 b Noisy data => large error surface average distance better defined than the

2 b Noisy data => large error surface average distance better defined than the distribution

data 0001 Excellent definition of three populations … complex assymetric population

data 0001 Excellent definition of three populations … complex assymetric population

data 0002 one population, very well defined

data 0002 one population, very well defined

data 0003 • components A and B very well defined: narrow distributions assymetric population

data 0003 • components A and B very well defined: narrow distributions assymetric population • component (c) badly defined component

last 0001

last 0001

last 0002 Spikes are not always spikes! two components one very narrow

last 0002 Spikes are not always spikes! two components one very narrow

last 0003 two components one very narrow

last 0003 two components one very narrow

last 0004

last 0004

DATA 1 low modulation depth, very long distance and very broad

DATA 1 low modulation depth, very long distance and very broad

DATA 2 three components, chi 2 impovement 6 x from 2 components. one extremely

DATA 2 three components, chi 2 impovement 6 x from 2 components. one extremely sharp