deletions | additions       diff --git a/Abstract.tex b/Abstract.tex  index bf196d3..170840d 100644  --- a/Abstract.tex  +++ b/Abstract.tex 
...
Single-molecule FRET experiments allows to probe the distance between two fluorescent labels (\textit{donor} and \textit{acceptor}) on the 3-10nm range. In the commonly employed confocal geometry, molecules are free to diffuse in a solution. When a molecule crosses the excitation volume it emits a burst of photons that can be detected by single-photon detectors (SPADs). In a nutshell, assessing the relative intensity of the donor and acceptor signal in each bursts it allows to infer their distance. smFRET experiments permit to study binding-unbinding processes or conformational changes of biomolecules and have proven to be an unvaluable tool in studying many cellular processes \cite{Kapanidis_2006}.  The data analysis Analyzing smFRET experiments  involves processing identifing  the photon timestamps single-molecule bursts  in (at least) two spectral channels (donor a continuous stream of photon timestamps, estimating the background and other correction factors, filtering  and acceptor). extracting the corrected FRET efficiencies for each sub-populations in the sample.  Although smFRET experiments are routinely performed by many labs around the world, no standard or reference  software exists.The  FRETBursts software presented described  in this paper represents the firstcomplete  opensource software implementation of all the common state-of-the-art algorithms  for smFRET data analysis implementing most of analysis. We follow  the state-of-the-art algorithms. highest standard in software development to ensure that the source is easy to read, well documented and thoroghly tested. Moreover, in an effort to lower the barriers to computational reproducibility, we embrace a modern workflow based on ipython notebooks that allows to capture the whole process from raw data to figures within a single document.  We aim to build a foundationand heavily documenting the sorce code we strive We strive to provide a software that is easy to use, read and extend. The source code is heavily commented and the algorithms documented and a the reference documentation is automatically build from inline docstrings. Example notebooks and data files are provided to makes easy to get started. The development takes place openly on github, a unit-test suite is automatically run after each commit,