Diplomarbeit Torsten Lüdge

Theory

Inverse Problems and Bayes Ansatz

FRET Trajectory estimation: Window method, Optimal Random Walk

(Probability to Observe Photon Type Y, given distance r: p(Y|r), p(Y|E)).

Forward-Backward and Expectation-Maximization Algorithm

Markov chains, Markov property

Hidden Markov Models (Discrete hidden state, discrete output)

Hidden Markov Models with Gauss Output

Hidden Markov Models with SDE Output

FRET Experimentals

Physical Principle (FRET)

Experimental Setup (Single Molecules, Fluorescence Microscrope, Beamsplitter, Photodetectors)

Measurement Errors (X-Talk, Background Noise, Gamma factor)

and Corrections (in Terms of p(Y|r))

Trajectory Estimation (from photons to E(t) and r(t))

Comparison of Window and Optimal Random Walk on artificial Trajectories

Comparison of Window and Optimal Random Walk on experimental Trajectories

Hidden Markov Models (Get transition matrix and distribution of E(t) or r(t) in each state)

Application of HMM-Gauss and HMM-SDE to artificial Trajectories

Application of HMM-Gauss and HMM-SDE to experimental Trajectories

Variation of Window length, Central limit theorm ,..

Properties of T (transition matrix): Lifetimes of states.

Suggestion of new experiments.

Conclusions

Comments

 

Zeitplan

ToDo Juli(25) Aug(25) Sept(25) Okt(10)
LyX Alle SubSubtitles 1.Vorversion 1.Version Final
Data Korrektur Anwenden Alle Traces ausrechnen ... ...
Programm Correction/SDE generate Metamacs? Standalone?
Pictures unkorrigert/korrigier Traces
time window/FW BW Histograms
HMM Würfel Verweigungsmodell Diels Alderase (VMD)
time window/FW BW FRET-Potential
sonst Ressourcen Liste Schöll vorlegen Nienhaus&Schöll vorlegen Abgeben
Topic revision: r3 - 15 Jun 2012, AntoniaMey
 
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