FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2912157247> ?p ?o ?g. }

• W2912157247 abstract "Abstract Prediction of residue-residue distance relationships (e.g. contacts) has become the key direction to advance protein tertiary structure prediction since 2014 CASP11 experiment, while deep learning has revolutionized the technology for contact and distance distribution prediction since its debut in 2012 CASP10 experiment. During 2018 CASP13 experiment, we enhanced our MULTICOM protein structure prediction system with three major components: contact distance prediction based on deep convolutional neural networks, contact distance-driven template-free ( ab initio ) modeling, and protein model ranking empowered by deep learning and contact prediction, in addition to an update of other components such as template library, sequence database, and alignment tools. Our experiment demonstrates that contact distance prediction and deep learning methods are the key reasons that MULTICOM was ranked 3rd out of all 98 predictors in both template-free and template-based protein structure modeling in CASP13. Deep convolutional neural network can utilize global information in pairwise residue-residue features such as co-evolution scores to substantially improve inter-residue contact distance prediction, which played a decisive role in correctly folding some free modeling and hard template-based modeling targets from scratch. Deep learning also successfully integrated 1D structural features, 2D contact information, and 3D structural quality scores to improve protein model quality assessment, where the contact prediction was demonstrated to consistently enhance ranking of protein models for the first time. The success of MULTICOM system in the CASP13 experiment clearly shows that protein contact distance prediction and model selection driven by powerful deep learning holds the key of solving protein structure prediction problem. However, there are still major challenges in accurately predicting protein contact distance when there are few homologous sequences to generate co-evolutionary signals, folding proteins from noisy contact distances, and ranking models of hard targets." @default.
• W2912157247 created "2019-02-21" @default.
• W2912157247 creator A5022495891 @default.
• W2912157247 creator A5044354277 @default.
• W2912157247 creator A5083523912 @default.
• W2912157247 creator A5085487073 @default.
• W2912157247 date "2019-02-17" @default.
• W2912157247 modified "2023-10-13" @default.
• W2912157247 title "Protein tertiary structure modeling driven by deep learning and contact distance prediction in CASP13" @default.
• W2912157247 cites W1663797894 @default.
• W2912157247 cites W1763545885 @default.
• W2912157247 cites W1998199521 @default.
• W2912157247 cites W1999613945 @default.
• W2912157247 cites W2008545402 @default.
• W2912157247 cites W2008708467 @default.
• W2912157247 cites W2013238066 @default.
• W2912157247 cites W2017421343 @default.
• W2912157247 cites W2036149515 @default.
• W2912157247 cites W2048310584 @default.
• W2912157247 cites W2051210555 @default.
• W2912157247 cites W2059886783 @default.
• W2912157247 cites W2061042699 @default.
• W2912157247 cites W2062123114 @default.
• W2912157247 cites W2062693912 @default.
• W2912157247 cites W2075095565 @default.
• W2912157247 cites W2088608587 @default.
• W2912157247 cites W2106868489 @default.
• W2912157247 cites W2114340287 @default.
• W2912157247 cites W2116672918 @default.
• W2912157247 cites W2117451312 @default.
• W2912157247 cites W2119550029 @default.
• W2912157247 cites W2119843684 @default.
• W2912157247 cites W2123085274 @default.
• W2912157247 cites W2131474431 @default.
• W2912157247 cites W2135621733 @default.
• W2912157247 cites W2138755951 @default.
• W2912157247 cites W2140454691 @default.
• W2912157247 cites W2140673705 @default.
• W2912157247 cites W2144046885 @default.
• W2912157247 cites W2145268834 @default.
• W2912157247 cites W2145991251 @default.
• W2912157247 cites W2158714788 @default.
• W2912157247 cites W2161151688 @default.
• W2912157247 cites W2176135968 @default.
• W2912157247 cites W2201713963 @default.
• W2912157247 cites W2280207768 @default.
• W2912157247 cites W2287165934 @default.
• W2912157247 cites W2344557669 @default.
• W2912157247 cites W2385735394 @default.
• W2912157247 cites W2406171343 @default.
• W2912157247 cites W2411608355 @default.
• W2912157247 cites W2419006500 @default.
• W2912157247 cites W2560695073 @default.
• W2912157247 cites W2565608178 @default.
• W2912157247 cites W2574496196 @default.
• W2912157247 cites W2607268717 @default.
• W2912157247 cites W2751535614 @default.
• W2912157247 cites W2765742208 @default.
• W2912157247 cites W2769882797 @default.
• W2912157247 cites W2778001245 @default.
• W2912157247 cites W2808950571 @default.
• W2912157247 cites W2905812122 @default.
• W2912157247 cites W2906084236 @default.
• W2912157247 cites W2949867299 @default.
• W2912157247 cites W4236236547 @default.
• W2912157247 cites W4244821183 @default.
• W2912157247 doi "https://doi.org/10.1101/552422" @default.
• W2912157247 hasPublicationYear "2019" @default.
• W2912157247 type Work @default.
• W2912157247 sameAs 2912157247 @default.
• W2912157247 citedByCount "7" @default.
• W2912157247 countsByYear W29121572472019 @default.
• W2912157247 countsByYear W29121572472020 @default.
• W2912157247 countsByYear W29121572472021 @default.
• W2912157247 crossrefType "posted-content" @default.
• W2912157247 hasAuthorship W2912157247A5022495891 @default.
• W2912157247 hasAuthorship W2912157247A5044354277 @default.
• W2912157247 hasAuthorship W2912157247A5083523912 @default.
• W2912157247 hasAuthorship W2912157247A5085487073 @default.
• W2912157247 hasBestOaLocation W29121572471 @default.
• W2912157247 hasConcept C108583219 @default.
• W2912157247 hasConcept C119857082 @default.
• W2912157247 hasConcept C153180895 @default.
• W2912157247 hasConcept C154945302 @default.
• W2912157247 hasConcept C18051474 @default.
• W2912157247 hasConcept C184898388 @default.
• W2912157247 hasConcept C185592680 @default.
• W2912157247 hasConcept C189430467 @default.
• W2912157247 hasConcept C41008148 @default.
• W2912157247 hasConcept C47701112 @default.
• W2912157247 hasConcept C50644808 @default.
• W2912157247 hasConcept C55493867 @default.
• W2912157247 hasConcept C66153294 @default.
• W2912157247 hasConcept C75599170 @default.
• W2912157247 hasConcept C81363708 @default.
• W2912157247 hasConceptScore W2912157247C108583219 @default.
• W2912157247 hasConceptScore W2912157247C119857082 @default.
• W2912157247 hasConceptScore W2912157247C153180895 @default.
• W2912157247 hasConceptScore W2912157247C154945302 @default.
• W2912157247 hasConceptScore W2912157247C18051474 @default.

• next