cdf97b3df98fc12b2b58df8c44a1b0e532fc27de
jnavarr5
  Tue May 12 15:52:55 2020 -0700
Updating http to https for panTro2, uiLinks cronjob.

diff --git src/hg/makeDb/trackDb/nscanGene.html src/hg/makeDb/trackDb/nscanGene.html
index 46fba02..7cceccd 100644
--- src/hg/makeDb/trackDb/nscanGene.html
+++ src/hg/makeDb/trackDb/nscanGene.html
@@ -7,31 +7,31 @@
 
 <H2>Methods</H2>
 <P>
 N-SCAN combines biological-signal modeling in the target genome sequence along
 with information from a multiple-genome alignment to generate de novo gene
 predictions. It extends the TWINSCAN target-informant genome pair to allow for
 an arbitrary number of informant sequences as well as richer models of
 sequence evolution. N-SCAN models the phylogenetic relationships between the
 aligned genome sequences, context-dependent substitution rates, insertions,
 and deletions.
 </P>
 <P>${informant}</P>
 
 <H2>Credits</H2>
 <P>
-Thanks to <A HREF="http://mblab.wustl.edu/" 
+Thanks to <A HREF="https://mblab.wustl.edu/" 
 TARGET=_blank>Michael Brent's Computational Genomics Group</A> at Washington 
 University St. Louis for providing this data.
 </P>
 <p>
 Special thanks for this implementation of N-SCAN to Aaron Tenney in
 the Brent lab, and Robert Zimmermann, currently at Max F. Perutz
 Laboratories in Vienna, Austria.
 </p>
 
 <H2>References</H2>
 <p>
 Gross SS, Brent MR.
 <a href="https://www.liebertpub.com/doi/pdf/10.1089/cmb.2006.13.379" target="_blank">
 Using multiple alignments to improve gene prediction</a>.
 <em>J Comput Biol</em>. 2006 Mar;13(2):379-93.