Theoretical models: Difference between revisions

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~~'''~~AlphaFold2 Methods~~''':~~ AlphaFold2 uses deep machine learning from the [[Protein Data Bank]] and sequence databases, and relies heavily on distances between beta-carbons<ref name="senior202001" />. AlphaFold2 is trained from data in the PDB to predict "the distances between pairs of residues, which convey more information about the structure than contact predictions."<ref name="senior202001" /> By one estimate<ref name="rubiera" />, "the DeepMind team had roughly two orders of magnitude more computational resources" than did academic groups competing in CASP 14. Further information about methods was provided by AlQuraishi<ref name="alquraishi" />.

====AlphaFold2 Methods====

AlphaFold2 uses deep machine learning from the [[Protein Data Bank]] and sequence databases, and relies heavily on distances between beta-carbons<ref name="senior202001" />. AlphaFold2 is trained from data in the PDB to predict "the distances between pairs of residues, which convey more information about the structure than contact predictions."<ref name="senior202001" /> By one estimate<ref name="rubiera" />, "the DeepMind team had roughly two orders of magnitude more computational resources" than did academic groups competing in CASP 14. Further information about methods was provided by AlQuraishi<ref name="alquraishi" />.

====CASP 14 Global Distance Test Results====

Theoretical models: Difference between revisions

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-'''AlphaFold2 Methods''': AlphaFold2 uses deep machine learning from the [[Protein Data Bank]] and sequence databases, and relies heavily on distances between beta-carbons<ref name="senior202001" />. AlphaFold2 is trained from data in the PDB to predict "the distances between pairs of residues, which convey more information about the structure than contact predictions."<ref name="senior202001" /> By one estimate<ref name="rubiera" />, "the DeepMind team had roughly two orders of magnitude more computational resources" than did academic groups competing in CASP 14. Further information about methods was provided by AlQuraishi<ref name="alquraishi" />.
+====AlphaFold2 Methods====
+AlphaFold2 uses deep machine learning from the [[Protein Data Bank]] and sequence databases, and relies heavily on distances between beta-carbons<ref name="senior202001" />. AlphaFold2 is trained from data in the PDB to predict "the distances between pairs of residues, which convey more information about the structure than contact predictions."<ref name="senior202001" /> By one estimate<ref name="rubiera" />, "the DeepMind team had roughly two orders of magnitude more computational resources" than did academic groups competing in CASP 14. Further information about methods was provided by AlQuraishi<ref name="alquraishi" />.
 ====CASP 14 Global Distance Test Results====