deletions | additions       diff --git a/section_Results_Consistent_with_previous__.tex b/section_Results_Consistent_with_previous__.tex  index 3ea78fb..21537d0 100644  --- a/section_Results_Consistent_with_previous__.tex  +++ b/section_Results_Consistent_with_previous__.tex 
...
\section*{Results}  Consistent with previous studies \cite{Tiikkainen_2009}, we find the MUV dataset to be a challenging target for shape-based screening with few targets demonstrating AUCs far from random performance. Overall FOMS either matched or exceeded the virtual screening performance of VAMS while retaining most of the benefits of pre-aligned molecules. Specifically, it is orders of magnitude faster than the optimizing alignment of RDKit suggesting, at a minimum, that FOMS is a viable method for rapidly pre-screening large libraries. In general, the pareto-optimal frontier of the shape constraint queries (highlighted with solid circles in the provided ROC plots) delineated virtual screen performance equivalent or better to a full shape similarity search. search while performing queries orders of magnitude faster.