Matches in SemOpenAlex for { <https://semopenalex.org/work/W4384261731> ?p ?o ?g. }
Showing items 1 to 55 of
55
with 100 items per page.
- W4384261731 abstract "Ribozymes, RNA molecules with distinct 3D structures and catalytic activity, have widespread applications in synthetic biology and therapeutics. However, relatively little research has focused on leveraging deep learning to enhance our understanding of ribozymes. This study implements Word2Vec, an unsupervised learning technique for natural language processing, to learn ribozyme embeddings. Ribo2Vec was trained on over 9,000 diverse ribozymes, learning to map sequences to 128 and 256-dimensional vector spaces. Using Ribo2Vec, sequence embeddings for five classes of ribozymes (hatchet, pistol, hairpin, hovlinc, and twister sister) were calculated. Principal component analysis demonstrated the ability of these embeddings to distinguish between ribozyme classes. Furthermore, a simple SVM classifier trained on ribozyme embeddings showed promising results in accurately classifying ribozyme types. Our results suggest that the embedding vectors contained meaningful information about ribozymes. Interestingly, 256-dimensional embeddings behaved similarly to 128-dimensional embeddings, suggesting that a lower dimension vector space is generally sufficient to capture ribozyme features. This approach demonstrates the potential of Word2Vec for bioinformatics, opening new avenues for ribozyme research. Future research includes using a Transformer-based method to learn RNA embeddings, which can capture long-range interactions between nucleotides." @default.
- W4384261731 created "2023-07-14" @default.
- W4384261731 creator A5088692854 @default.
- W4384261731 date "2023-07-08" @default.
- W4384261731 modified "2023-10-17" @default.
- W4384261731 title "NLP Meets RNA: Unsupervised Embedding Learning for Ribozymes with Word2Vec" @default.
- W4384261731 doi "https://doi.org/10.48550/arxiv.2307.05537" @default.
- W4384261731 hasPublicationYear "2023" @default.
- W4384261731 type Work @default.
- W4384261731 citedByCount "0" @default.
- W4384261731 crossrefType "posted-content" @default.
- W4384261731 hasAuthorship W4384261731A5088692854 @default.
- W4384261731 hasBestOaLocation W43842617311 @default.
- W4384261731 hasConcept C104317684 @default.
- W4384261731 hasConcept C119857082 @default.
- W4384261731 hasConcept C1342335 @default.
- W4384261731 hasConcept C154945302 @default.
- W4384261731 hasConcept C2776461190 @default.
- W4384261731 hasConcept C41008148 @default.
- W4384261731 hasConcept C41608201 @default.
- W4384261731 hasConcept C54355233 @default.
- W4384261731 hasConcept C67705224 @default.
- W4384261731 hasConcept C70721500 @default.
- W4384261731 hasConcept C76346623 @default.
- W4384261731 hasConcept C80444323 @default.
- W4384261731 hasConcept C86803240 @default.
- W4384261731 hasConceptScore W4384261731C104317684 @default.
- W4384261731 hasConceptScore W4384261731C119857082 @default.
- W4384261731 hasConceptScore W4384261731C1342335 @default.
- W4384261731 hasConceptScore W4384261731C154945302 @default.
- W4384261731 hasConceptScore W4384261731C2776461190 @default.
- W4384261731 hasConceptScore W4384261731C41008148 @default.
- W4384261731 hasConceptScore W4384261731C41608201 @default.
- W4384261731 hasConceptScore W4384261731C54355233 @default.
- W4384261731 hasConceptScore W4384261731C67705224 @default.
- W4384261731 hasConceptScore W4384261731C70721500 @default.
- W4384261731 hasConceptScore W4384261731C76346623 @default.
- W4384261731 hasConceptScore W4384261731C80444323 @default.
- W4384261731 hasConceptScore W4384261731C86803240 @default.
- W4384261731 hasLocation W43842617311 @default.
- W4384261731 hasOpenAccess W4384261731 @default.
- W4384261731 hasPrimaryLocation W43842617311 @default.
- W4384261731 hasRelatedWork W1481423171 @default.
- W4384261731 hasRelatedWork W1972033253 @default.
- W4384261731 hasRelatedWork W2009133056 @default.
- W4384261731 hasRelatedWork W2064293171 @default.
- W4384261731 hasRelatedWork W2116687527 @default.
- W4384261731 hasRelatedWork W2152397220 @default.
- W4384261731 hasRelatedWork W2400719429 @default.
- W4384261731 hasRelatedWork W2900607420 @default.
- W4384261731 hasRelatedWork W3196684861 @default.
- W4384261731 hasRelatedWork W4319936794 @default.
- W4384261731 isParatext "false" @default.
- W4384261731 isRetracted "false" @default.
- W4384261731 workType "article" @default.