fe64746a8641a29b07cb641312297726e6ed4468
hiram
  Wed Sep 7 15:50:58 2022 -0700
adding description page for TOGA tracks refs #29982

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+<h2>Description</h2>
+<p>
+<b>T</b>ool to infer <b>O</b>rthologs from <b>G</b>enome <b>A</b>lignments
+</p>
+<p>
+<b>TOGA</b> is a new method that integrates gene annotation, inferring orthologs
+and classifying genes as intact or lost.
+</p>
+<p>
+<b>TOGA</b> implements a novel machine learning based paradigm to infer
+orthologous genes between related species and to accurately distinguish
+orthologs from paralogs or processed pseudogenes.
+</p>
+
+<h2>Credits</h2>
+<p>
+This data was prepared by the <a href='https://tbg.senckenberg.de/hillerlab/'
+target=_blank>Michael Hiller Lab</a>
+</p>
+
+<h2>References</h2>
+<p>
+The <b>TOGA</b> software is available from
+<a href='https://github.com/hillerlab/TOGA'
+target=_blank>github.com/hillerlab/TOGA</a>
+</p>
+
+<p>
+Kirilenko BM, Munegowda C, Osipova E, Jebb D, Sharma V, Blumer M, Morales A,
+Ahmed AW, Kontopoulos DG, Hilgers L, Zoonomia Consortium, Hiller M.
+Integrating gene annotation with orthology inference at scale.
+<a href='https://math.mit.edu/seminars/compbiosem/spring22/hiller_michael.pdf'
+target=_blank><em>Under Review</em></a>
+</p>