FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3191324478> ?p ?o ?g. }

• W3191324478 endingPage "117002" @default.
• W3191324478 startingPage "117002" @default.
• W3191324478 abstract "A deep learning (DL) method for quickly predicting surface charge density profiles (σ-profile) and cavity volumes (VCOSMO) of molecules for the COSMO-SAC model is developed. The molecular fingerprints are derived from the encoder state of a Transformer model pre-trained on the ChEMBL database, which allows transfer learning from large-scale unlabeled data and improve generalization performance by developing better molecular fingerprints for building models with significantly smaller datasets. Employing the pre-trained molecular fingerprints, a convolutional neural network (CNN) model for the σ-profile and VCOSMO prediction is trained and tested on the VT-2005 database. The obtained Transformer-CNN model presents superior performance to the GC-COSMO approach and enables the prediction of σ-profile and VCOSMO of millions of molecules in only a few minutes. Taking advantages of the model, a high-throughput solvent screening framework based on COSMO-SAC is further proposed and exemplified by searching sustainable solvent for the deterpenation process of citrus essential oils." @default.
• W3191324478 created "2021-08-16" @default.
• W3191324478 creator A5030462752 @default.
• W3191324478 creator A5055191233 @default.
• W3191324478 creator A5058493921 @default.
• W3191324478 date "2021-12-01" @default.
• W3191324478 modified "2023-10-18" @default.
• W3191324478 title "Transformer-convolutional neural network for surface charge density profile prediction: Enabling high-throughput solvent screening with COSMO-SAC" @default.
• W3191324478 cites W1495546099 @default.
• W3191324478 cites W1832693441 @default.
• W3191324478 cites W1967357378 @default.
• W3191324478 cites W1975147762 @default.
• W3191324478 cites W1976883040 @default.
• W3191324478 cites W1983107047 @default.
• W3191324478 cites W1997415372 @default.
• W3191324478 cites W1998144999 @default.
• W3191324478 cites W2000614400 @default.
• W3191324478 cites W2029714637 @default.
• W3191324478 cites W2038702914 @default.
• W3191324478 cites W2042007894 @default.
• W3191324478 cites W2072398524 @default.
• W3191324478 cites W2073328513 @default.
• W3191324478 cites W2073791189 @default.
• W3191324478 cites W2103888387 @default.
• W3191324478 cites W2149747120 @default.
• W3191324478 cites W2166277125 @default.
• W3191324478 cites W2320034101 @default.
• W3191324478 cites W2326408897 @default.
• W3191324478 cites W2411076832 @default.
• W3191324478 cites W2558999090 @default.
• W3191324478 cites W2564211371 @default.
• W3191324478 cites W2564811697 @default.
• W3191324478 cites W2564865157 @default.
• W3191324478 cites W2587800494 @default.
• W3191324478 cites W2621742623 @default.
• W3191324478 cites W2763484703 @default.
• W3191324478 cites W2764120290 @default.
• W3191324478 cites W2765224015 @default.
• W3191324478 cites W2801449321 @default.
• W3191324478 cites W2901476322 @default.
• W3191324478 cites W2903010511 @default.
• W3191324478 cites W2904656109 @default.
• W3191324478 cites W2947764583 @default.
• W3191324478 cites W2963295149 @default.
• W3191324478 cites W2964199361 @default.
• W3191324478 cites W2969341076 @default.
• W3191324478 cites W2972498877 @default.
• W3191324478 cites W2972608805 @default.
• W3191324478 cites W2973114758 @default.
• W3191324478 cites W2979753613 @default.
• W3191324478 cites W2987620995 @default.
• W3191324478 cites W2990443801 @default.
• W3191324478 cites W3001060390 @default.
• W3191324478 cites W3026751302 @default.
• W3191324478 cites W3030978062 @default.
• W3191324478 cites W3032409190 @default.
• W3191324478 cites W3042354185 @default.
• W3191324478 cites W3044798947 @default.
• W3191324478 cites W3089022612 @default.
• W3191324478 cites W3098269892 @default.
• W3191324478 cites W3103092523 @default.
• W3191324478 cites W3119875191 @default.
• W3191324478 cites W4246725120 @default.
• W3191324478 doi "https://doi.org/10.1016/j.ces.2021.117002" @default.
• W3191324478 hasPublicationYear "2021" @default.
• W3191324478 type Work @default.
• W3191324478 sameAs 3191324478 @default.
• W3191324478 citedByCount "19" @default.
• W3191324478 countsByYear W31913244782022 @default.
• W3191324478 countsByYear W31913244782023 @default.
• W3191324478 crossrefType "journal-article" @default.
• W3191324478 hasAuthorship W3191324478A5030462752 @default.
• W3191324478 hasAuthorship W3191324478A5055191233 @default.
• W3191324478 hasAuthorship W3191324478A5058493921 @default.
• W3191324478 hasConcept C108583219 @default.
• W3191324478 hasConcept C111919701 @default.
• W3191324478 hasConcept C118505674 @default.
• W3191324478 hasConcept C119599485 @default.
• W3191324478 hasConcept C119857082 @default.
• W3191324478 hasConcept C127413603 @default.
• W3191324478 hasConcept C153180895 @default.
• W3191324478 hasConcept C154945302 @default.
• W3191324478 hasConcept C165801399 @default.
• W3191324478 hasConcept C185592680 @default.
• W3191324478 hasConcept C41008148 @default.
• W3191324478 hasConcept C50644808 @default.
• W3191324478 hasConcept C55493867 @default.
• W3191324478 hasConcept C63222358 @default.
• W3191324478 hasConcept C66322947 @default.
• W3191324478 hasConcept C74187038 @default.
• W3191324478 hasConcept C81363708 @default.
• W3191324478 hasConceptScore W3191324478C108583219 @default.
• W3191324478 hasConceptScore W3191324478C111919701 @default.
• W3191324478 hasConceptScore W3191324478C118505674 @default.
• W3191324478 hasConceptScore W3191324478C119599485 @default.
• W3191324478 hasConceptScore W3191324478C119857082 @default.
• W3191324478 hasConceptScore W3191324478C127413603 @default.
• W3191324478 hasConceptScore W3191324478C153180895 @default.

• next