Commit b91390c4 by waldispuhl

### minor changes

parent 34e29daa
 ... ... @@ -127,7 +127,7 @@ \author{Vladimir Reinharz$^1$, Yann Ponty$^2$, J\'er\^{o}me Waldisp\"{u}hl$^1$} \address{$^1$ School of Computer Science, McGill University, Montreal, Canada\\\small $^2$ Laboratoire d'informatique, \'Ecole Polytechnique, Palaiseau, France.} \address{$^1$ School of Computer Science, McGill University, Montreal, Canada\\$^2$ Laboratoire d'informatique, \'Ecole Polytechnique, Palaiseau, France.} \history{Received on XXXXX; revised on XXXXX; accepted on XXXXX} ... ... @@ -286,7 +286,8 @@ Since both negative and positive correlations can indicate positions of interest, we use two different, $\zeta^-$ and $\zeta^+$, thresholds for the \NPMI{}s. $\zeta^+$ will be a bound on the positive values of the \NPMI and $\zeta^-$ on the negative ones. Due to the high number of possible combinations, \NPMI{}s having values $-1$ are frequent and uninformative. They are discarded. For those loops deemed as regions of interest, we predict that the {\color{red} set of} positions having an \NPMI above $\zeta^+$ {\color{red} or} below $\zeta^-$ {\color{red} are binding interfaces} while the others {\color{red}are} not. {\color{red} For those loops deemed as regions of interest, we predict that the set of positions with an \NPMI above $\zeta^+$ or below $\zeta^-$ are nucleotides in binding interfaces while the others are not.} {\removelatexerror \begin{algorithm} \DontPrintSemicolon ... ...
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