deletions | additions       diff --git a/Overview.tex b/Overview.tex  index 857d7a7..0385f61 100644  --- a/Overview.tex  +++ b/Overview.tex 
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Additionally, implementations of population dynamics analysis such  as Burst Variance Analysis (BVA)~\cite{Torella_2011} and two-channel  kernel density distribution estimator (2CDE)~\cite{Tomov_2012}  are available as FRETBursts notebooks. notebooks  (\href{http://nbviewer.jupyter.org/github/tritemio/FRETBursts_notebooks/blob/master/notebooks/Example%20-%20Burst%20Variance%20Analysis.ipynb}{BVA link},  \href{http://nbviewer.jupyter.org/github/tritemio/FRETBursts_notebooks/blob/master/notebooks/Example%20-%202CDE%20Method.ipynb}{2CDE link}).  \subsection{Software Availability}  FRETBursts is hosted and openly developed on GitHub. FRETBursts homepage  diff --git a/bibliography/biblio.bib b/bibliography/biblio.bib  index 9ca81dc..b07385f 100644  --- a/bibliography/biblio.bib  +++ b/bibliography/biblio.bib 
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@incollection{sisamakis_accurate_2010,  edition = {1},  title = {Accurate {Single}-{Molecule} {FRET} {Studies} {Using} {Multiparameter} {Fluorescence} {Detection}},  volume = {475},  isbn = {978-0-12-381482-1},  url = {http://www.ncbi.nlm.nih.gov/pubmed/20627168},  booktitle = {Methods in {Enzymology}},  publisher = {Elsevier Inc.},  author = {Sisamakis, Evangelos and Valeri, Alessandro and Kalinin, Stanislav and Rothwell, Paul J and Seidel, C. A. M.},  month = jan,  year = {2010},  pages = {455--514},  }  @article{santoso_probing_2009,  title = {Probing biomolecular structures and dynamics of single molecules using in-gel alternating-laser excitation.},  volume = {81},  url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2799195&tool=pmcentrez&rendertype=abstract},  doi = {10.1021/ac901423e},  number = {23},  journal = {Analytical chemistry},  author = {Santoso, Yusdi and Kapanidis, Achillefs N},  month = dec,  year = {2009},  pages = {9561--70},  }  @article{hoffmann_quantifying_2011,  title = {Quantifying heterogeneity and conformational dynamics from single molecule {FRET} of diffusing molecules: recurrence analysis of single particles ({RASP}).},  volume = {13},  url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3378030&tool=pmcentrez&rendertype=abstract},  doi = {10.1039/c0cp01911a},  number = {5},  journal = {Physical Chemistry Chemical Physics},  author = {Hoffmann, Armin and Nettels, Daniel and Clark, Jennifer and Borgia, Alessandro and Radford, Sheena E and Clarke, Jane and Schuler, Benjamin},  month = feb,  year = {2011}  }  @incollection{gopich_theory_2011,  address = {Hoboken, NJ, USA},  series = {Advances in {Chemical} {Physics}},  title = {Theory of {Single}-{Molecule} {FRET} {Efficiency} {Histograms}},  volume = {146},  isbn = {978-1-118-13137-4},  url = {http://doi.wiley.com/10.1002/9781118131374},  booktitle = {Single-{Molecule} {Biophysics}: {Experiment} and {Theory}, {Volume} 146},  publisher = {John Wiley \& Sons, Inc.},  author = {Gopich, Irina V and Szabo, Attila},  editor = {Komatsuzaki, Tamiki and Kawakami, Masaru and Takahashi, Satoshi and Yang, Haw and Silbey, Robert J.},  month = nov,  year = {2011},  pages = {245--297},  }  @article{Kalinin2010,  author = {Stanislav Kalinin and Evangelos Sisamakis and Steven W. Magennis and Suren Felekyan and Claus A. M. Seidel},  title = {On the Origin of Broadening of Single-Molecule FRET Efficiency Distributions beyond Shot Noise Limits},  journal = {The Journal of Physical Chemistry B},  volume = {114},  number = {18},  pages = {6197-6206},  year = {2010},  doi = {10.1021/jp100025v},  URL = {http://dx.doi.org/10.1021/jp100025v},  }  @article{Gopich2009,  author = {Irina V. Gopich and Attila Szabo},  title = {Decoding the Pattern of Photon Colors in Single-Molecule FRET},  journal = {The Journal of Physical Chemistry B},  volume = {113},  number = {31},  pages = {10965-10973},  year = {2009},  doi = {10.1021/jp903671p},  URL = {http://dx.doi.org/10.1021/jp903671p},  }  @article{Stephens1974,  author = {Stephens, M. A.},  doi = {10.2307/2286009},  diff --git a/fitting_2.tex b/fitting_2.tex  index fcffa6d..c77a628 100644  --- a/fitting_2.tex  +++ b/fitting_2.tex 
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(\href{http://nbviewer.jupyter.org/github/tritemio/FRETBursts_notebooks/blob/master/notebooks/FRETBursts%20-%20us-ALEX%20smFRET%20burst%20analysis.ipynb#FRET-fit:-in-depth-example}{link}).  Users can also refer to the comprehensive lmfit's documentation  (\href{http://lmfit.github.io/lmfit-py/}{link}).  \subsection{FRET Dynamics}  \label{sec:dynamics}  FRET peaks resolved from FRET histograms correspond to different FRET  populations. However determining whether these populations are due to static  heterogeneity (different D-A distances, Förster radius, etc.) or a  dynamic equilibrium, requires further analysis.  Shot-noise analysis (SNA)~\cite{Nir_2006} or probability  distribution analysis (PDA)~\cite{Antonik2006} allow to compute  the minimal width of a FRET peak originating from a single  FRET efficiency. Typically, several mechanisms  contribute to the broadening of the experimental FRET peak  beyond the shot-noise limit. For example, heterogeneities in the sample  (resulting in a distribution of Förster radiuses)  or actual conformational changes (resulting in a distribution  of D-A distances) can cause FRET peak broadening~\cite{sisamakis_accurate_2010}.  Kalinin~\cite{Kalinin2010} and Santoso~\cite{santoso_probing_2009}  extended the PDA approach to estimate conversion rates between different  states by comparing FRET histograms as a function of the time-bin size.  Gopich and Szabo~\cite{Gopich2009, gopich_theory_2011} developed  a related method to compute conversion rates using  a likelihood function which depends on photon timestamps (overcoming  the time binning and FRET histogramming step).  Hoffman~\cite{hoffmann_quantifying_2011} extended the  timescale of detectable kinetics by considering multiple subsequent bursts  and computing the probability that two nearby bursts are originating from  the same molecules.  Other two related methods are Burst Variance Analysis  (BVA)~\cite{Torella_2011} and  kernel density distribution estimator (2CDE)~\cite{Tomov_2012}  which allow to discriminate between static heterogeneity  and sub-millisecond dynamics by extracting information  from the photon distribution within each burst.  The last two methods, BVA and 2CDE, are implemented  in two notebooks included with FRETBursts  (\href{http://nbviewer.jupyter.org/github/tritemio/FRETBursts_notebooks/blob/master/notebooks/Example%20-%20Burst%20Variance%20Analysis.ipynb}{BVA link},  \href{http://nbviewer.jupyter.org/github/tritemio/FRETBursts_notebooks/blob/master/notebooks/Example%20-%202CDE%20Method.ipynb}{2CDE link}).  The other methods are not currently implemented in FRETBursts.  However, motivated users can implement their favorite method  leveraging the burst manipulation functions in FRETBursts  and the standard scientific Python libraries. We encourage researchers  coding new methods with FRETBursts to share their contributions and  to integrate their work in FRETBursts in order to benefit the entire community.  The next section, takes the BVA method as an example for showing how to  perform low-level manipulation of timestamps and bursts data.  An additional example showing how to split bursts in constant time-bins  can be found in the respective FRETBursts notebook  (\href{http://nbviewer.jupyter.org/github/tritemio/FRETBursts_notebooks/blob/master/notebooks/Example%20-%20Working%20with%20timestamps%20and%20bursts.ipynb}{link}).  These examples server as a guide for implementing new methods  using FRETBursts.