deletions | additions
diff --git a/FRETBursts authorea latex/full_article.tex b/FRETBursts authorea latex/full_article.tex
index a4cf6ac..c3e464c 100644
--- a/FRETBursts authorea latex/full_article.tex
+++ b/FRETBursts authorea latex/full_article.tex
...
contains links to the various resources. Installation instructions can be found in the
Reference Documentation (\href{http://fretbursts.readthedocs.org/en/latest/getting_started.html}{link}).
A description of FRETBursts execution using Jupyter notebooks is reported
in~\ref{sec:notebook}. in~\nameref{sec:notebook}. % SI_link
Detailed information on development style, testing strategies and
contributions guidelines are reported
in~\ref{sec:dev}. in~\nameref{sec:dev}. % SI_link
Finally, to facilitate evaluation and comparison with other software,
we set up an on-line services allowing to execute FRETBursts
without requiring any installation on the user's computer (\href{https://github.com/tritemio/FRETBursts_notebooks#run-online}{link}).
...
so that the bursts with largest sizes will have the largest weights.
Using size as weights (instead of any other monotonically increasing function
of size) can be justified noticing that the variance of bursts proximity ratio (PR) is
inversely proportional to the burst size
(see~\ref{sec:burstweights_theory} (see~\nameref{sec:burstweights_theory} for details). % SI_link
In general, a weighting scheme is used for building efficient estimators for a population
parameter (e.g. the population FRET efficiency $E_p$).
...
as possible to reduce statistical noise.
As a practical example, by fixing the burst size threshold to a low value (e.g. 10-20 photons)
and using weights, is possible to build a FRET histogram with well-defined FRET sub-populations peaks
without the need of searching an optimal burst-size threshold
(\ref{sec:burstweights_theory}). (\nameref{sec:burstweights_theory}).
\paragraph{Python details}
FRETBursts has the option to weight bursts using $\gamma$-corrected
...
\textit{Background estimation} section of the μs-ALEX tutorial
(\href{http://nbviewer.jupyter.org/github/tritemio/FRETBursts_notebooks/blob/master/notebooks/FRETBursts%20-%20us-ALEX%20smFRET%20burst%20analysis.ipynb#Background-estimation}{link}).
Finally, it is possible to use a slower but rigorous approach for finding the optimal
threshold as described
in~\ref{sec:bg_opt_th}. in~\nameref{sec:bg_opt_th}. % SI_link
FRETBursts provides two kinds of plots to represent the background. One shows the histograms
of inter-photon delays compared to the fitted exponential distribution, shown in
...
\end{lstlisting}
This command reflects the general form of plotting commands in FRETBursts
as described
in~\ref{sec:plotting}. in~\nameref{sec:plotting}. % SI_link
Here we only note that the argument \verb|period| is an integer specifying the background
period to be plotted (when omitted, the default is 0, i.e. the first period).
Figure~\ref{fig:bg_dist_all} allows to quickly identify pathological cases where the
...
\section{Conclusions}
\label{sec:conclusions}
FRETBursts is an open source and openly developed
(see~\ref{sec:dev}) (see~\nameref{sec:dev}) implementation % SI_link
of established smFRET burst analysis methods
made available to the single-molecule community.
It implements several novel concepts which improve the analysis results, such as
