fc524ed53987a5a3f5a2057fc99d2de751a7f132
jnavarr5
  Tue Feb 25 16:03:47 2020 -0800
Updating redirected links found for dm3, uiLinks cronjob.

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+++ src/hg/makeDb/trackDb/contrastGene.html
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 <H2>Description</H2>
 <P>
 This track shows protein-coding gene predictions generated by 
 <a href=http://contra.stanford.edu/contrast/ target="_blank">CONTRAST</a>.  
 Each predicted exon is colored according to confidence level: green (high
 confidence), orange (medium confidence), or red (low confidence).
 </P>
 
 <H2>Methods</H2>
 <P>
 CONTRAST predicts protein-coding genes from a multiple genomic
 alignment using a combination of discriminative machine learning techniques.  A two-stage approach is used, in which output from local classifiers is combined with a global model of gene structure.  CONTRAST is trained using a novel procedure designed to
 maximize expected coding region boundary detection accuracy.
 
 <P>
 Please see the 
 <a href=http://contra.stanford.edu/contrast/ target="_blank">CONTRAST web site</a> for details on how these predictions were generated and an estimate of accuracy. 
 
 <H2>Credits</H2>
 <P>
-Thanks to Samuel Gross of the <a href="http://www.serafimb.org/people.html" target="_blank">
+Thanks to Samuel Gross of the <a href="https://www.serafimb.org/people.html" target="_blank">
 Batzoglou lab</a> at Stanford University for providing these predictions.
 
 <H2>References</H2>
 <p>
 Gross SS, Do CB, Sirota M, Batzoglou S.
 <a href="https://genomebiology.biomedcentral.com/articles/10.1186/gb-2007-8-12-r269"
 target="_blank">CONTRAST: a discriminative, phylogeny-free approach to multiple informant de novo
 gene prediction</a>.
 <em>Genome Biol</em>. 2007;8(12):R269.
 PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/18096039" target="_blank">18096039</a>; PMC: <a
 href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2246271/" target="_blank">PMC2246271</a>
 </p>