Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386022012> ?p ?o ?g. }
- W4386022012 abstract "DNA N4-methylcytosine (4mC) is significantly involved in biological processes, such as DNA expression, repair, and replication. Therefore, accurate prediction methods are urgently needed. Deep learning methods have transformed applications that previously require sequencing expertise into engineering challenges that do not require expertise to solve. Here, we compare a variety of state-of-the-art deep learning models on six benchmark datasets to evaluate their performance in 4mC methylation site detection. We visualize the statistical analysis of the datasets and the performance of different deep-learning models. We conclude that deep learning can greatly expand the potential of methylation site prediction." @default.
- W4386022012 created "2023-08-22" @default.
- W4386022012 creator A5000266884 @default.
- W4386022012 creator A5020374752 @default.
- W4386022012 creator A5024040521 @default.
- W4386022012 creator A5028462736 @default.
- W4386022012 creator A5040384066 @default.
- W4386022012 date "2023-08-21" @default.
- W4386022012 modified "2023-09-26" @default.
- W4386022012 title "Comparative evaluation and analysis of DNA N4-methylcytosine methylation sites using deep learning" @default.
- W4386022012 cites W1498436455 @default.
- W4386022012 cites W1831033366 @default.
- W4386022012 cites W1832693441 @default.
- W4386022012 cites W2000225203 @default.
- W4386022012 cites W2074746593 @default.
- W4386022012 cites W2079735306 @default.
- W4386022012 cites W2098740506 @default.
- W4386022012 cites W2145975061 @default.
- W4386022012 cites W2152656267 @default.
- W4386022012 cites W2160530309 @default.
- W4386022012 cites W2257561185 @default.
- W4386022012 cites W2559588458 @default.
- W4386022012 cites W2737592062 @default.
- W4386022012 cites W2787427645 @default.
- W4386022012 cites W2883534252 @default.
- W4386022012 cites W2945027804 @default.
- W4386022012 cites W2951434717 @default.
- W4386022012 cites W2981572887 @default.
- W4386022012 cites W3004000061 @default.
- W4386022012 cites W3015957975 @default.
- W4386022012 cites W3037668068 @default.
- W4386022012 cites W3086030569 @default.
- W4386022012 cites W3102385171 @default.
- W4386022012 cites W3120734548 @default.
- W4386022012 cites W3125843200 @default.
- W4386022012 cites W3127238141 @default.
- W4386022012 cites W3137447770 @default.
- W4386022012 cites W3139253280 @default.
- W4386022012 cites W3164453494 @default.
- W4386022012 cites W3189610884 @default.
- W4386022012 cites W3190763963 @default.
- W4386022012 cites W3193614607 @default.
- W4386022012 cites W3198254086 @default.
- W4386022012 cites W3202017248 @default.
- W4386022012 cites W3204213738 @default.
- W4386022012 cites W3204360269 @default.
- W4386022012 cites W3207672631 @default.
- W4386022012 cites W3217082130 @default.
- W4386022012 cites W4200435161 @default.
- W4386022012 cites W4205177317 @default.
- W4386022012 cites W4207028073 @default.
- W4386022012 cites W4211219865 @default.
- W4386022012 cites W4281249267 @default.
- W4386022012 cites W4285492639 @default.
- W4386022012 cites W4288712766 @default.
- W4386022012 cites W4298119349 @default.
- W4386022012 cites W4303432141 @default.
- W4386022012 cites W4303628999 @default.
- W4386022012 cites W4306404289 @default.
- W4386022012 cites W4307447012 @default.
- W4386022012 cites W4309218736 @default.
- W4386022012 cites W4312827846 @default.
- W4386022012 cites W4313405519 @default.
- W4386022012 cites W4313561039 @default.
- W4386022012 cites W4321015480 @default.
- W4386022012 doi "https://doi.org/10.3389/fgene.2023.1254827" @default.
- W4386022012 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37671040" @default.
- W4386022012 hasPublicationYear "2023" @default.
- W4386022012 type Work @default.
- W4386022012 citedByCount "0" @default.
- W4386022012 crossrefType "journal-article" @default.
- W4386022012 hasAuthorship W4386022012A5000266884 @default.
- W4386022012 hasAuthorship W4386022012A5020374752 @default.
- W4386022012 hasAuthorship W4386022012A5024040521 @default.
- W4386022012 hasAuthorship W4386022012A5028462736 @default.
- W4386022012 hasAuthorship W4386022012A5040384066 @default.
- W4386022012 hasBestOaLocation W43860220121 @default.
- W4386022012 hasConcept C104317684 @default.
- W4386022012 hasConcept C108583219 @default.
- W4386022012 hasConcept C119857082 @default.
- W4386022012 hasConcept C12590798 @default.
- W4386022012 hasConcept C13280743 @default.
- W4386022012 hasConcept C132917006 @default.
- W4386022012 hasConcept C141231307 @default.
- W4386022012 hasConcept C150194340 @default.
- W4386022012 hasConcept C154945302 @default.
- W4386022012 hasConcept C159047783 @default.
- W4386022012 hasConcept C185798385 @default.
- W4386022012 hasConcept C190727270 @default.
- W4386022012 hasConcept C205649164 @default.
- W4386022012 hasConcept C2775926025 @default.
- W4386022012 hasConcept C33288867 @default.
- W4386022012 hasConcept C41008148 @default.
- W4386022012 hasConcept C41091548 @default.
- W4386022012 hasConcept C54355233 @default.
- W4386022012 hasConcept C552990157 @default.
- W4386022012 hasConcept C70721500 @default.
- W4386022012 hasConcept C86803240 @default.
- W4386022012 hasConceptScore W4386022012C104317684 @default.
- W4386022012 hasConceptScore W4386022012C108583219 @default.