Remove line number from copied results text

Author: jcass11

README.rst

@@ -39,7 +39,7 @@ We simulate particle diffusion in a range of homogeneous diffusion constants, an
 To assess the conditional feasibility of computationally detecting differences in diffusivity, we generate a landscape of the KL divergence between posteriors generated from pairs of simulations, with varying trajectory lengths and differences in diffusivity. To further correct for stochastic variations in simulations, the KL divergence reported for each entry in the landscape is the mean value from thousands of replicates. We find that, using this method, diffusivities differing by a factor of 1.5 or more can be easily distinguished when at least 50 timepoints are reported for each trajectory. This landscape offers a look-up table for estimating the number of frames that must be acquired experimentally to distinguish diffusivities to a desired precision. This framework could therefore play a valuable role in describing the feasibility of and requirements for experiments addressing the spatial heterogeneity of the intracellular diffusive environment. To address the affects of static localization error of punctate objects from microscopy images, we included Gaussian error to the particle location at each point in its trajectory. The standard deviation of this Gaussian determines the amount of localization error applied. Now, error in the ability to detect the underlying diffusion constant is a compound error due to the affects of both localization error and error in Bayesian estimation of the posterior maximum.
 
 **Conclusion**
-The spatial heterogeneity of diffusion may have major impacts in the transport ofessential cellular substrates but remains largely uncharacterized. To shed light on thefeasibility of resolving spatial from stochastic drivers of diffusive heterogeneity intrajectory data, we developed a framework for predicting our ability to detect differences in diffusivity, conditional on the amount of experimental data collected. Our framework can therefore be used to inform the design of experiments aimed to55characterize the spatial dependence of diffusivity across cells.
+The spatial heterogeneity of diffusion may have major impacts in the transport ofessential cellular substrates but remains largely uncharacterized. To shed light on thefeasibility of resolving spatial from stochastic drivers of diffusive heterogeneity intrajectory data, we developed a framework for predicting our ability to detect differences in diffusivity, conditional on the amount of experimental data collected. Our framework can therefore be used to inform the design of experiments aimed to characterize the spatial dependence of diffusivity across cells.
 
 
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