FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2750376939> ?p ?o ?g. }

• W2750376939 endingPage "155" @default.
• W2750376939 startingPage "142" @default.
• W2750376939 abstract "Predicting the β-sheet structure of a protein is one of the most important intermediate steps towards the identification of its tertiary structure. However, it is regarded as the primary bottleneck due to the presence of non-local interactions between several discontinuous regions in β-sheets. To achieve reliable long-range interactions, a promising approach is to enumerate and rank all β-sheet conformations for a given protein and find the one with the highest score. The problem with this solution is that the search space of the problem grows exponentially with respect to the number of β-strands. Additionally, brute-force calculation in this conformational space leads to dealing with a combinatorial explosion problem with intractable computational complexity. The main contribution of this paper is to generate and search the space of the problem efficiently to reduce the time complexity of the problem. To achieve this, two tree structures, called sheet-tree and grouping-tree, are proposed. They model the search space by breaking it into sub-problems. Then, an advanced dynamic programming is proposed that stores the intermediate results, avoids repetitive calculation by repeatedly uses them efficiently in successive steps and reduces the space of the problem by removing those intermediate results that will no longer be required in later steps. As a consequence, the following contributions have been made. Firstly, more accurate β-sheet structures are found by searching all possible conformations, and secondly, the time complexity of the problem is reduced by searching the space of the problem efficiently which makes the proposed method applicable to predict β-sheet structures with high number of β-strands. Experimental results on the BetaSheet916 dataset showed significant improvements of the proposed method in both execution time and the prediction accuracy in comparison with the state-of-the-art β-sheet structure prediction methods Moreover, we investigate the effect of different contact map predictors on the performance of the proposed method using BetaSheet1452 dataset. The source code is available at http://www.conceptsgate.com/BetaTop.rar." @default.
• W2750376939 created "2017-08-31" @default.
• W2750376939 creator A5000670364 @default.
• W2750376939 creator A5004938325 @default.
• W2750376939 creator A5042422813 @default.
• W2750376939 creator A5082103872 @default.
• W2750376939 date "2017-10-01" @default.
• W2750376939 modified "2023-09-25" @default.
• W2750376939 title "Protein β-sheet prediction using an efficient dynamic programming algorithm" @default.
• W2750376939 cites W1540530720 @default.
• W2750376939 cites W1969644422 @default.
• W2750376939 cites W1978172310 @default.
• W2750376939 cites W1981194976 @default.
• W2750376939 cites W1985420739 @default.
• W2750376939 cites W2008708467 @default.
• W2750376939 cites W2034859202 @default.
• W2750376939 cites W2045777307 @default.
• W2750376939 cites W2053691972 @default.
• W2750376939 cites W2064420001 @default.
• W2750376939 cites W2069852256 @default.
• W2750376939 cites W2074231493 @default.
• W2750376939 cites W2076768638 @default.
• W2750376939 cites W2098464924 @default.
• W2750376939 cites W2104467962 @default.
• W2750376939 cites W2107264799 @default.
• W2750376939 cites W2121374178 @default.
• W2750376939 cites W2122011799 @default.
• W2750376939 cites W2130479394 @default.
• W2750376939 cites W2131474431 @default.
• W2750376939 cites W2153187042 @default.
• W2750376939 cites W2159262772 @default.
• W2750376939 cites W2164583490 @default.
• W2750376939 cites W2165186407 @default.
• W2750376939 cites W2165766097 @default.
• W2750376939 cites W2166701319 @default.
• W2750376939 cites W2170882281 @default.
• W2750376939 cites W2197074115 @default.
• W2750376939 cites W2561366344 @default.
• W2750376939 cites W2577638289 @default.
• W2750376939 cites W2949867299 @default.
• W2750376939 cites W2963457143 @default.
• W2750376939 cites W2159507425 @default.
• W2750376939 doi "https://doi.org/10.1016/j.compbiolchem.2017.08.011" @default.
• W2750376939 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28881217" @default.
• W2750376939 hasPublicationYear "2017" @default.
• W2750376939 type Work @default.
• W2750376939 sameAs 2750376939 @default.
• W2750376939 citedByCount "5" @default.
• W2750376939 countsByYear W27503769392019 @default.
• W2750376939 countsByYear W27503769392021 @default.
• W2750376939 countsByYear W27503769392022 @default.
• W2750376939 crossrefType "journal-article" @default.
• W2750376939 hasAuthorship W2750376939A5000670364 @default.
• W2750376939 hasAuthorship W2750376939A5004938325 @default.
• W2750376939 hasAuthorship W2750376939A5042422813 @default.
• W2750376939 hasAuthorship W2750376939A5082103872 @default.
• W2750376939 hasConcept C111919701 @default.
• W2750376939 hasConcept C113174947 @default.
• W2750376939 hasConcept C11413529 @default.
• W2750376939 hasConcept C114614502 @default.
• W2750376939 hasConcept C115908005 @default.
• W2750376939 hasConcept C125583679 @default.
• W2750376939 hasConcept C126255220 @default.
• W2750376939 hasConcept C149635348 @default.
• W2750376939 hasConcept C159985019 @default.
• W2750376939 hasConcept C164226766 @default.
• W2750376939 hasConcept C179799912 @default.
• W2750376939 hasConcept C192562407 @default.
• W2750376939 hasConcept C204323151 @default.
• W2750376939 hasConcept C207024777 @default.
• W2750376939 hasConcept C2778572836 @default.
• W2750376939 hasConcept C2780513914 @default.
• W2750376939 hasConcept C33923547 @default.
• W2750376939 hasConcept C41008148 @default.
• W2750376939 hasConcept C80444323 @default.
• W2750376939 hasConceptScore W2750376939C111919701 @default.
• W2750376939 hasConceptScore W2750376939C113174947 @default.
• W2750376939 hasConceptScore W2750376939C11413529 @default.
• W2750376939 hasConceptScore W2750376939C114614502 @default.
• W2750376939 hasConceptScore W2750376939C115908005 @default.
• W2750376939 hasConceptScore W2750376939C125583679 @default.
• W2750376939 hasConceptScore W2750376939C126255220 @default.
• W2750376939 hasConceptScore W2750376939C149635348 @default.
• W2750376939 hasConceptScore W2750376939C159985019 @default.
• W2750376939 hasConceptScore W2750376939C164226766 @default.
• W2750376939 hasConceptScore W2750376939C179799912 @default.
• W2750376939 hasConceptScore W2750376939C192562407 @default.
• W2750376939 hasConceptScore W2750376939C204323151 @default.
• W2750376939 hasConceptScore W2750376939C207024777 @default.
• W2750376939 hasConceptScore W2750376939C2778572836 @default.
• W2750376939 hasConceptScore W2750376939C2780513914 @default.
• W2750376939 hasConceptScore W2750376939C33923547 @default.
• W2750376939 hasConceptScore W2750376939C41008148 @default.
• W2750376939 hasConceptScore W2750376939C80444323 @default.
• W2750376939 hasLocation W27503769391 @default.
• W2750376939 hasLocation W27503769392 @default.
• W2750376939 hasOpenAccess W2750376939 @default.
• W2750376939 hasPrimaryLocation W27503769391 @default.

• next