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10.1155/2018/7607384 http://scihub22266oqcxt.onion/10.1155/2018/7607384 C6031167!6031167!30026759     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Adv+Bioinformatics 2018 ; 2018 (ä): ä Nephropedia Template TP {{tp|p=30026759|t=2018. A Novel Framework for Ab Initio Coarse Protein Structure Prediction |pdf=|usr=}}{{30026759}} gab.com Text A Novel Framework for Ab Initio Coarse Protein Structure Prediction JO: Adv Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=30026759 #FOAvip Hydrophobic-Polar model is a simplified representation of Protein Structure Prediction (PSP) problem. However, even with the HP model, the PSP problem remains NP-complete. This work proposes a systematic and problem specific design for operators of the evolutionary program which hybrids with local search hill climbing, to efficiently explore the search space of PSP and thereby obtain an optimum conformation. The proposed algorithm achieves this by incorporating the following novel features: (i) new initialization method which generates only valid individuals with (rather than random) better fitness values; (ii) use of probability-based selection operators that limit the local convergence; (iii) use of secondary structure based mutation operator that makes the structure more closely to the laboratory determined structure; and (iv) incorporating all the above-mentioned features developed a complete two-tier framework. The developed framework builds the protein conformation on the square and triangular lattice. The test has been performed using benchmark sequences, and a comparative evaluation is done with various state-of-the-art algorithms. Moreover, in addition to hypothetical test sequences, we have tested protein sequences deposited in protein database repository. It has been observed that the proposed framework has shown superior performance regarding accuracy (fitness value) and speed (number of generations needed to attain the final conformation). The concepts used to enhance the performance are generic and can be used with any other population-based search algorithm such as genetic algorithm, ant colony optimization, and immune algorithm. Twit Text FOAVip A Novel Framework for Ab Initio Coarse Protein Structure Prediction ????Adv Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=30026759 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=30026759 #FOAvip English Wikipedia <ref>{{Cite pmid|30026759}}</ref> A Novel Framework for Ab Initio Coarse Protein Structure Prediction #MMPMID30026759 Dubey SP; Balaji S; Kini NG; Sathish Kumar M Adv Bioinformatics 2018[]; 2018 (ä): ä PMID30026759show ga Hydrophobic-Polar model is a simplified representation of Protein Structure Prediction (PSP) problem. However, even with the HP model, the PSP problem remains NP-complete. This work proposes a systematic and problem specific design for operators of the evolutionary program which hybrids with local search hill climbing, to efficiently explore the search space of PSP and thereby obtain an optimum conformation. The proposed algorithm achieves this by incorporating the following novel features: (i) new initialization method which generates only valid individuals with (rather than random) better fitness values; (ii) use of probability-based selection operators that limit the local convergence; (iii) use of secondary structure based mutation operator that makes the structure more closely to the laboratory determined structure; and (iv) incorporating all the above-mentioned features developed a complete two-tier framework. The developed framework builds the protein conformation on the square and triangular lattice. The test has been performed using benchmark sequences, and a comparative evaluation is done with various state-of-the-art algorithms. Moreover, in addition to hypothetical test sequences, we have tested protein sequences deposited in protein database repository. It has been observed that the proposed framework has shown superior performance regarding accuracy (fitness value) and speed (number of generations needed to attain the final conformation). The concepts used to enhance the performance are generic and can be used with any other population-based search algorithm such as genetic algorithm, ant colony optimization, and immune algorithm. äA Novel Framework for Ab Initio Coarse Protein Structure Prediction (epmc).pdf DeepDyve Pubget Overpricing