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10.1007/978-1-4939-3572-7_24 http://scihub22266oqcxt.onion/10.1007/978-1-4939-3572-7_24 C4894841!4894841!27115648     free     free     free       Methods+Mol+Biol 2016 ; 1415 (ä): 463-76 Nephropedia Template TP {{tp|p=27115648|t=2016. Protein Residue Contacts and Prediction Methods |pdf=|usr=}}{{27115648}} gab.com Text Protein Residue Contacts and Prediction Methods JO: Methods Mol Biol http://www.kidney.de/pget.php?&tw=1&pmid=27115648 #FOAvip In the field of computational structural proteomics, contact predictions have shown new prospects of solving the longstanding problem of ab initio protein structure prediction. In the last few years, application of deep learning algorithms and availability of large protein sequence databases, combined with improvement in methods that derive contacts from multiple sequence alignments, have shown a huge increase in the precision of contact prediction. In addition, these predicted contacts have also been used to build three-dimensional models from scratch.In this chapter, we briefly discuss many elements of protein residue?residue contacts and the methods available for prediction, focusing on a state-of-the-art contact prediction tool, DNcon. Illustrating with a case study, we describe how DNcon can be used to make ab initio contact predictions for a given protein sequence and discuss how the predicted contacts may be analyzed and evaluated. Twit Text FOAVip Protein Residue Contacts and Prediction Methods ????Methods Mol Biol http://www.kidney.de/pget.php?&tw=1&pmid=27115648 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27115648 #FOAvip English Wikipedia <ref>{{Cite pmid|27115648}}</ref> Protein Residue Contacts and Prediction Methods #MMPMID27115648 Adhikari B; Cheng J Methods Mol Biol 2016[]; 1415 (ä): 463-76 PMID27115648show ga In the field of computational structural proteomics, contact predictions have shown new prospects of solving the longstanding problem of ab initio protein structure prediction. In the last few years, application of deep learning algorithms and availability of large protein sequence databases, combined with improvement in methods that derive contacts from multiple sequence alignments, have shown a huge increase in the precision of contact prediction. In addition, these predicted contacts have also been used to build three-dimensional models from scratch.In this chapter, we briefly discuss many elements of protein residue?residue contacts and the methods available for prediction, focusing on a state-of-the-art contact prediction tool, DNcon. Illustrating with a case study, we describe how DNcon can be used to make ab initio contact predictions for a given protein sequence and discuss how the predicted contacts may be analyzed and evaluated. äProtein Residue Contacts and Prediction Methods (epmc).pdf DeepDyve Pubget Overpricing