User:Nir London/FunHunt: Difference between revisions

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==FunHunt==

FunHunt <ref>London N., Schueler-Furman O. (2008) Funnel hunting in a rough terrain: learning and discriminating native energy funnels. Structure. 16:269-79. </ref><ref>London N., Schueler-Furman O. (2007) Assessing the energy landscape of CAPRI targets by FunHunt. Proteins. 69:809-15</ref>is a classifier of correct protein-protein complex orientations. The input to FunHunt are two possible orientations of a complex. A local docking run is performed on the two complexes using RosettaDock. FunHunt then uses features gathered from these docking runs - representing the local energy landscapes of the orientations, and chooses the near-native orientation among both (assuming that one of the orientations is the near native one).

FunHunt <ref>London N., Schueler-Furman O. (2008) Funnel hunting in a rough terrain: learning and discriminating native energy funnels. Structure. 16:269-79. </ref><ref>London N., Schueler-Furman O. (2007) Assessing the energy landscape of CAPRI targets by FunHunt. Proteins. 69:809-15</ref> is a classifier of correct protein-protein complex orientations. The input to FunHunt are two possible orientations of a complex. A local docking run is performed on the two complexes using RosettaDock. FunHunt then uses features gathered from these docking runs - representing the local energy landscapes of the orientations, and chooses the near-native orientation among both (assuming that one of the orientations is the near native one).

FunHunt is available via the web. Try it! [http://funhunt.furmanlab.cs.huji.ac.il].

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 ==FunHunt==
-FunHunt <ref>London N., Schueler-Furman O. (2008) Funnel hunting in a rough terrain: learning and discriminating native energy funnels. Structure. 16:269-79. </ref><ref>London N., Schueler-Furman O. (2007) Assessing the energy landscape of CAPRI targets by FunHunt. Proteins. 69:809-15</ref>is a classifier of correct protein-protein complex orientations. The input to FunHunt are two possible orientations of a complex. A local docking run is performed on the two complexes using RosettaDock. FunHunt then uses features gathered from these docking runs - representing the local energy landscapes of the orientations, and chooses the near-native orientation among both (assuming that one of the orientations is the near native one).
+FunHunt <ref>London N., Schueler-Furman O. (2008) Funnel hunting in a rough terrain: learning and discriminating native energy funnels. Structure. 16:269-79. </ref><ref>London N., Schueler-Furman O. (2007) Assessing the energy landscape of CAPRI targets by FunHunt. Proteins. 69:809-15</ref> is a classifier of correct protein-protein complex orientations. The input to FunHunt are two possible orientations of a complex. A local docking run is performed on the two complexes using RosettaDock. FunHunt then uses features gathered from these docking runs - representing the local energy landscapes of the orientations, and chooses the near-native orientation among both (assuming that one of the orientations is the near native one).
+FunHunt is available via the web. Try it! [http://funhunt.furmanlab.cs.huji.ac.il].