deletions | additions       diff --git a/section_Implementing_Burst_Variance_Analysis__.tex b/section_Implementing_Burst_Variance_Analysis__.tex  index e7537d4..c15aa9e 100644  --- a/section_Implementing_Burst_Variance_Analysis__.tex  +++ b/section_Implementing_Burst_Variance_Analysis__.tex 
...
FRET histograms could show more information than just mean FRET efficiencies. Broad FRET distributions might be attributed to 1) the mixture of multiple species with static but different FRET efficiencies, 2) single species with dynamic fluctuations between multiple FRET states, or 3) a combination of the two cases. Burst Variance Analysis (BVA) is an analysis method for single molecule FRET experiments, developed to detect molecular dynamics~\cite{Torella_2011}. It has been successfully implemented to identify heterogeneities in FRET histograms due to dynamic processes of biomolecules in millisecond time scale~\cite{Torella_2011, Robb_2013}.  The concept of BVA iscomparing an expected standard deviation($\sigma_E$) for a burst to calculated standard deviations($s_E$) of sub-bursts comprised of \textit{n} consecutive photons within the burst in order  to figure out whether the observed broadness of FRET distributions are owing to the molecular dynamics~\cite{Torella_2011}. dynamics, by comparison of a calculated standard deviation ($s_E$) of FRET efficiencies for sub-bursts ,comprised of \textit{n} consecutive photons within the burst, from a mean FRET efficiency for a burst to an expected standard deviation($\sigma_E$) based on shot noise limited distribution~\cite{Torella_2011}.  If the broadness originates from different molecules with static but different FRET efficiencies, $\sigma_E$ of each individual molecule are only affected by shot noise and $s_E$ for any sub-burst will follow a binomial distribution. $$ n_t = n_a + \gamma\,n_d$$