FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4366753183> ?p ?o ?g. }

• W4366753183 endingPage "107874" @default.
• W4366753183 startingPage "107874" @default.
• W4366753183 abstract "B-Cell epitopes (BCEs) can identify and bind with receptor proteins (antigens) to initiate an immune response against pathogens. Understanding antigen-antibody binding interactions has many applications in biotechnology and biomedicine, including designing antibodies, therapeutics, and vaccines. Lab-based experimental identification of these proteins is time-consuming and challenging. Computational techniques have been proposed to discover BCEs, but most lack of significant accomplishments. This work uses classical and deep learning models (DLMs) with sequence-based features to predict immunity stimulator BCEs from proteomics sequences. The proposed convolutional neural network-based model outperforms other models with an accuracy (ACC) of 0.878, an F-measure of 0.871, and an area under the receiver operating characteristic curve (AUC) of 0.945. The proposed strategy achieves 58.7% better results on average than other state-of-the-art approaches based on the Mathews Correlation Coefficient (MCC) results. The established model is accessible through a web application located at http://deeplbcepred.pythonanywhere.com." @default.
• W4366753183 created "2023-04-24" @default.
• W4366753183 creator A5016603327 @default.
• W4366753183 creator A5019971091 @default.
• W4366753183 creator A5075858344 @default.
• W4366753183 creator A5088232762 @default.
• W4366753183 date "2023-06-01" @default.
• W4366753183 modified "2023-09-26" @default.
• W4366753183 title "DeepBCE: Evaluation of deep learning models for identification of immunogenic B-cell epitopes" @default.
• W4366753183 cites W1967311984 @default.
• W4366753183 cites W1976801077 @default.
• W4366753183 cites W2004490529 @default.
• W4366753183 cites W2005779329 @default.
• W4366753183 cites W2034126715 @default.
• W4366753183 cites W2035014358 @default.
• W4366753183 cites W2048848017 @default.
• W4366753183 cites W2053707749 @default.
• W4366753183 cites W2059178238 @default.
• W4366753183 cites W2061151008 @default.
• W4366753183 cites W2064675550 @default.
• W4366753183 cites W2087230890 @default.
• W4366753183 cites W2091852797 @default.
• W4366753183 cites W2097874743 @default.
• W4366753183 cites W2107432340 @default.
• W4366753183 cites W2137575262 @default.
• W4366753183 cites W2148853951 @default.
• W4366753183 cites W2160397907 @default.
• W4366753183 cites W2161301244 @default.
• W4366753183 cites W2165224041 @default.
• W4366753183 cites W2611314002 @default.
• W4366753183 cites W2767250699 @default.
• W4366753183 cites W2777980778 @default.
• W4366753183 cites W2790400419 @default.
• W4366753183 cites W2803011470 @default.
• W4366753183 cites W2889276168 @default.
• W4366753183 cites W2896188973 @default.
• W4366753183 cites W2905397045 @default.
• W4366753183 cites W2906411860 @default.
• W4366753183 cites W2911964244 @default.
• W4366753183 cites W2928389720 @default.
• W4366753183 cites W2951624434 @default.
• W4366753183 cites W2964199361 @default.
• W4366753183 cites W2982150996 @default.
• W4366753183 cites W3004222371 @default.
• W4366753183 cites W3010127039 @default.
• W4366753183 cites W3018838420 @default.
• W4366753183 cites W3019617034 @default.
• W4366753183 cites W3086901785 @default.
• W4366753183 cites W3109724560 @default.
• W4366753183 cites W3119775068 @default.
• W4366753183 cites W3127812974 @default.
• W4366753183 cites W3137649039 @default.
• W4366753183 cites W3159663509 @default.
• W4366753183 cites W3162566731 @default.
• W4366753183 cites W4200299925 @default.
• W4366753183 cites W4224130789 @default.
• W4366753183 cites W4247382206 @default.
• W4366753183 cites W4248215625 @default.
• W4366753183 cites W4285807029 @default.
• W4366753183 cites W4312732123 @default.
• W4366753183 doi "https://doi.org/10.1016/j.compbiolchem.2023.107874" @default.
• W4366753183 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37126975" @default.
• W4366753183 hasPublicationYear "2023" @default.
• W4366753183 type Work @default.
• W4366753183 citedByCount "1" @default.
• W4366753183 countsByYear W43667531832023 @default.
• W4366753183 crossrefType "journal-article" @default.
• W4366753183 hasAuthorship W4366753183A5016603327 @default.
• W4366753183 hasAuthorship W4366753183A5019971091 @default.
• W4366753183 hasAuthorship W4366753183A5075858344 @default.
• W4366753183 hasAuthorship W4366753183A5088232762 @default.
• W4366753183 hasBestOaLocation W43667531831 @default.
• W4366753183 hasConcept C108583219 @default.
• W4366753183 hasConcept C116834253 @default.
• W4366753183 hasConcept C119857082 @default.
• W4366753183 hasConcept C147483822 @default.
• W4366753183 hasConcept C154945302 @default.
• W4366753183 hasConcept C195616568 @default.
• W4366753183 hasConcept C203014093 @default.
• W4366753183 hasConcept C41008148 @default.
• W4366753183 hasConcept C58471807 @default.
• W4366753183 hasConcept C59822182 @default.
• W4366753183 hasConcept C60644358 @default.
• W4366753183 hasConcept C66782513 @default.
• W4366753183 hasConcept C70721500 @default.
• W4366753183 hasConcept C81363708 @default.
• W4366753183 hasConcept C86803240 @default.
• W4366753183 hasConceptScore W4366753183C108583219 @default.
• W4366753183 hasConceptScore W4366753183C116834253 @default.
• W4366753183 hasConceptScore W4366753183C119857082 @default.
• W4366753183 hasConceptScore W4366753183C147483822 @default.
• W4366753183 hasConceptScore W4366753183C154945302 @default.
• W4366753183 hasConceptScore W4366753183C195616568 @default.
• W4366753183 hasConceptScore W4366753183C203014093 @default.
• W4366753183 hasConceptScore W4366753183C41008148 @default.
• W4366753183 hasConceptScore W4366753183C58471807 @default.
• W4366753183 hasConceptScore W4366753183C59822182 @default.
• W4366753183 hasConceptScore W4366753183C60644358 @default.

• next