FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313893898> ?p ?o ?g. }

• W4313893898 endingPage "137" @default.
• W4313893898 startingPage "137" @default.
• W4313893898 abstract "Structure-function relationships in proteins have been one of the crucial scientific topics in recent research. Heme proteins have diverse and pivotal biological functions. Therefore, clarifying their structure-function correlation is significant to understand their functional mechanism and is informative for various fields of science. In this study, we constructed convolutional neural network models for predicting protein functions from the tertiary structures of heme-binding sites (active sites) of heme proteins to examine the structure-function correlation. As a result, we succeeded in the classification of oxygen-binding protein (OB), oxidoreductase (OR), proteins with both functions (OB-OR), and electron transport protein (ET) with high accuracy. Although the misclassification rate for OR and ET was high, the rates between OB and ET and between OB and OR were almost zero, indicating that the prediction model works well between protein groups with quite different functions. However, predicting the function of proteins modified with amino acid mutation(s) remains a challenge. Our findings indicate a structure-function correlation in the active site of heme proteins. This study is expected to be applied to the prediction of more detailed protein functions such as catalytic reactions." @default.
• W4313893898 created "2023-01-10" @default.
• W4313893898 creator A5015137270 @default.
• W4313893898 creator A5020353235 @default.
• W4313893898 creator A5051431208 @default.
• W4313893898 creator A5056487724 @default.
• W4313893898 creator A5056515301 @default.
• W4313893898 creator A5091037890 @default.
• W4313893898 date "2023-01-09" @default.
• W4313893898 modified "2023-10-14" @default.
• W4313893898 title "Prediction of Protein Function from Tertiary Structure of the Active Site in Heme Proteins by Convolutional Neural Network" @default.
• W4313893898 cites W1499450468 @default.
• W4313893898 cites W1969142598 @default.
• W4313893898 cites W1971552026 @default.
• W4313893898 cites W1982855811 @default.
• W4313893898 cites W1986026982 @default.
• W4313893898 cites W2004436328 @default.
• W4313893898 cites W2012698109 @default.
• W4313893898 cites W2021017431 @default.
• W4313893898 cites W2027140236 @default.
• W4313893898 cites W2027432077 @default.
• W4313893898 cites W2028323326 @default.
• W4313893898 cites W2030776726 @default.
• W4313893898 cites W2067873880 @default.
• W4313893898 cites W2069582231 @default.
• W4313893898 cites W2075841103 @default.
• W4313893898 cites W2083353493 @default.
• W4313893898 cites W2088437224 @default.
• W4313893898 cites W2091897848 @default.
• W4313893898 cites W2092059009 @default.
• W4313893898 cites W2100032379 @default.
• W4313893898 cites W2103613886 @default.
• W4313893898 cites W2110149903 @default.
• W4313893898 cites W2114850508 @default.
• W4313893898 cites W2130479394 @default.
• W4313893898 cites W2131479899 @default.
• W4313893898 cites W2142585562 @default.
• W4313893898 cites W2147988069 @default.
• W4313893898 cites W2153153865 @default.
• W4313893898 cites W2161088350 @default.
• W4313893898 cites W2168172687 @default.
• W4313893898 cites W2503686053 @default.
• W4313893898 cites W2742394249 @default.
• W4313893898 cites W2752399242 @default.
• W4313893898 cites W2769893400 @default.
• W4313893898 cites W2889060167 @default.
• W4313893898 cites W2914877211 @default.
• W4313893898 cites W2952988108 @default.
• W4313893898 cites W2995720795 @default.
• W4313893898 cites W2996071945 @default.
• W4313893898 cites W3036890741 @default.
• W4313893898 cites W3091024207 @default.
• W4313893898 cites W3163144368 @default.
• W4313893898 cites W3164046276 @default.
• W4313893898 cites W3183475563 @default.
• W4313893898 cites W3186118520 @default.
• W4313893898 cites W3210151021 @default.
• W4313893898 cites W4213346714 @default.
• W4313893898 cites W4214944872 @default.
• W4313893898 cites W4220781522 @default.
• W4313893898 cites W4280601022 @default.
• W4313893898 cites W4289522376 @default.
• W4313893898 cites W4292714375 @default.
• W4313893898 cites W4293008833 @default.
• W4313893898 cites W4376043580 @default.
• W4313893898 cites W649328397 @default.
• W4313893898 doi "https://doi.org/10.3390/biom13010137" @default.
• W4313893898 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36671521" @default.
• W4313893898 hasPublicationYear "2023" @default.
• W4313893898 type Work @default.
• W4313893898 citedByCount "1" @default.
• W4313893898 countsByYear W43138938982023 @default.
• W4313893898 crossrefType "journal-article" @default.
• W4313893898 hasAuthorship W4313893898A5015137270 @default.
• W4313893898 hasAuthorship W4313893898A5020353235 @default.
• W4313893898 hasAuthorship W4313893898A5051431208 @default.
• W4313893898 hasAuthorship W4313893898A5056487724 @default.
• W4313893898 hasAuthorship W4313893898A5056515301 @default.
• W4313893898 hasAuthorship W4313893898A5091037890 @default.
• W4313893898 hasBestOaLocation W43138938981 @default.
• W4313893898 hasConcept C104317684 @default.
• W4313893898 hasConcept C14036430 @default.
• W4313893898 hasConcept C18051474 @default.
• W4313893898 hasConcept C181199279 @default.
• W4313893898 hasConcept C185592680 @default.
• W4313893898 hasConcept C207060522 @default.
• W4313893898 hasConcept C2776217839 @default.
• W4313893898 hasConcept C2986374874 @default.
• W4313893898 hasConcept C41183919 @default.
• W4313893898 hasConcept C47701112 @default.
• W4313893898 hasConcept C55493867 @default.
• W4313893898 hasConcept C62614982 @default.
• W4313893898 hasConcept C70721500 @default.
• W4313893898 hasConcept C75599170 @default.
• W4313893898 hasConcept C86803240 @default.
• W4313893898 hasConcept C95444343 @default.
• W4313893898 hasConceptScore W4313893898C104317684 @default.
• W4313893898 hasConceptScore W4313893898C14036430 @default.

• next