Merge pull request #159 from iab-reader1/patch-1

fix misspelling

Author: Greg Caporaso

book/fundamentals/pairwise-alignment.md

@@ -503,7 +503,7 @@ So there you have it: the basics of pairwise sequence alignment, which is easily
 
 ### Smith-Waterman local alignment with affine gap scoring <link src='976169'/>
 
-The second limitation of the our simple alignment algorithm, and one that is also present in our version of Smith-Waterman as implemented above, is that all gaps are scored equally whether they represent the opening of a new insertion/deletion, or the extension of an existing insertion/deletion. This isn't ideal based on what we know about how insertion/deletion events occur (see [this discussion of replication slippage](http://www.ncbi.nlm.nih.gov/books/NBK21114/)). Instead, **we might want to incur a large penalty for opening a gap, but a smaller penalty for extending a gap**. To do this, **we need to make two small changes to our scoring scheme**. When we compute the score for a gap, we should incurr a *gap open penalty* if the previous max score was derived from inserting a gap character in the same sequence. If we represent our traceback matrix as $T$, our gap open penalty as $d^0$, and our gap extend penalty as $d^e$, our scoring scheme would look like the following:
+The second limitation of the our simple alignment algorithm, and one that is also present in our version of Smith-Waterman as implemented above, is that all gaps are scored equally whether they represent the opening of a new insertion/deletion, or the extension of an existing insertion/deletion. This isn't ideal based on what we know about how insertion/deletion events occur (see [this discussion of replication slippage](http://www.ncbi.nlm.nih.gov/books/NBK21114/)). Instead, **we might want to incur a large penalty for opening a gap, but a smaller penalty for extending a gap**. To do this, **we need to make two small changes to our scoring scheme**. When we compute the score for a gap, we should incur a *gap open penalty* if the previous max score was derived from inserting a gap character in the same sequence. If we represent our traceback matrix as $T$, our gap open penalty as $d^0$, and our gap extend penalty as $d^e$, our scoring scheme would look like the following:
 
 $$
 F(i, j) = max \left(\begin{align}