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10.1109/TCBB.2016.2543721 http://scihub22266oqcxt.onion/10.1109/TCBB.2016.2543721 C5071113!5071113 !27008671     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=27008671 &cmd=llinks): Failed to open stream: HTTP request failed! 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An Effective Computational Method Incorporating Multiple Secondary Structure Predictions in Topology Determination for Cryo-EM Images |pdf=|usr=}}{{27008671 }} gab.com Text An Effective Computational Method Incorporating Multiple Secondary Structure Predictions in Topology Determination for Cryo-EM Images JO: IEEE/ACM Trans Comput Biol Bioinform http://www.kidney.de/pget.php?&tw=1&pmid=27008671 #FOAvip A key idea in de novo modeling of a medium-resolution density image obtained from cryo-electron microscopy is to compute the optimal mapping between the secondary structure traces observed in the density image and those predicted on the protein sequence. When secondary structures are not determined precisely, either from the image or from the amino acid sequence of the protein, the computational problem becomes more complex. We present an efficient method that addresses the secondary structure placement problem in presence of multiple secondary structure predictions and computes the optimal mapping. We tested the method using 12 simulated images from ?-proteins and two Cryo-EM images of ?-? proteins. We observed that the rank of the true topologies is consistently improved by using multiple secondary structure predictions instead of a single prediction. The results show that the algorithm is robust and works well even when errors/misses in the predicted secondary structures are present in the image or the sequence. The results also show that the algorithm is efficient and is able to handle proteins with as many as 33 helices. Twit Text FOAVip An Effective Computational Method Incorporating Multiple Secondary Structure Predictions in Topology Determination for Cryo-EM Images ????IEEE/ACM Trans Comput Biol Bioinform http://www.kidney.de/pget.php?&tw=1&pmid=27008671 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27008671 #FOAvip English Wikipedia <ref>{{Cite pmid|27008671 }}</ref> An Effective Computational Method Incorporating Multiple Secondary Structure Predictions in Topology Determination for Cryo-EM Images #MMPMID27008671 Biswas A ; Ranjan D ; Zubair M ; Zeil S ; Nasr KA ; He J IEEE/ACM Trans Comput Biol Bioinform 2017[May]; 14 (3 ): 578-586 PMID27008671 show ga A key idea in de novo modeling of a medium-resolution density image obtained from cryo-electron microscopy is to compute the optimal mapping between the secondary structure traces observed in the density image and those predicted on the protein sequence. When secondary structures are not determined precisely, either from the image or from the amino acid sequence of the protein, the computational problem becomes more complex. We present an efficient method that addresses the secondary structure placement problem in presence of multiple secondary structure predictions and computes the optimal mapping. We tested the method using 12 simulated images from ?-proteins and two Cryo-EM images of ?-? proteins. We observed that the rank of the true topologies is consistently improved by using multiple secondary structure predictions instead of a single prediction. The results show that the algorithm is robust and works well even when errors/misses in the predicted secondary structures are present in the image or the sequence. The results also show that the algorithm is efficient and is able to handle proteins with as many as 33 helices. |Algorithms [MESH] |Computational Biology/*methods [MESH] |Cryoelectron Microscopy/*methods [MESH] |Image Processing, Computer-Assisted/*methods [MESH] |Models, Molecular [MESH] |Protein Structure, Secondary [MESH]An Effective Computational Method Incorporating Multiple Secondary Str(epmc).pdf DeepDyve Pubget Overpricing