FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385563495> ?p ?o ?g. }

• W4385563495 abstract "Abstract Motivation Next Generation Sequencing technologies make it possible to detect rare genetic variants in individual patients. Currently, more than a dozen software and web services have been created to predict the pathogenicity of variants related with changing of amino acid residues. Despite considerable efforts in this area, at the moment there is no ideal method to classify pathogenic and harmless variants, and the assessment of the pathogenicity is often contradictory. In this article, we propose to use peptides structural formulas of proteins as an amino acid residues substitutions description, rather than a single-letter code. This allowed us to investigate the effectiveness of chemoinformatics approach to assess the pathogenicity of variants associated with amino acid substitutions. Results The structure-activity relationships analysis relying on protein-specific data and atom centric substructural multilevel neighborhoods of atoms (MNA) descriptors of molecular fragments appeared to be suitable for predicting the pathogenic effect of single amino acid variants. MNA-based Naïve Bayes classifier algorithm, ClinVar and humsavar data were used for the creation of structure-activity relationships models for 10 proteins. The performance of the models was compared with 11 different predicting tools: 8 individual (SIFT 4G, Polyphen2 HDIV, MutationAssessor, PROVEAN, FATHMM, MVP, LIST-S2, MutPred) and 3 consensus (M-CAP, MetaSVM, MetaLR). The accuracy of MNA-based method varies for the proteins (AUC: 0.631–0.993; MCC: 0.191–0.891). It was similar for both the results of comparisons with the other individual predictors and third-party protein-specific predictors. For several proteins (BRCA1, BRCA2, COL1A2, and RYR1), the performance of the MNA-based method was outstanding, capable of capturing the pathogenic effect of structural changes in amino acid substitutions. Availability and implementation The datasets are available as supplemental data at Bioinformatics online. A python script to convert amino acid and nucleotide sequences from single-letter codes to SD files is available at https://github.com/SmirnygaTotoshka/SequenceToSDF. The authors provide trial licenses for MultiPASS software to interested readers upon request." @default.
• W4385563495 created "2023-08-05" @default.
• W4385563495 creator A5017099204 @default.
• W4385563495 creator A5027499841 @default.
• W4385563495 creator A5050528382 @default.
• W4385563495 creator A5065866115 @default.
• W4385563495 date "2023-08-01" @default.
• W4385563495 modified "2023-10-14" @default.
• W4385563495 title "Prediction of pathogenic single amino acid substitutions using molecular fragment descriptors" @default.
• W4385563495 cites W1563940013 @default.
• W4385563495 cites W1971835681 @default.
• W4385563495 cites W1997872815 @default.
• W4385563495 cites W2023350260 @default.
• W4385563495 cites W2039369430 @default.
• W4385563495 cites W2051978340 @default.
• W4385563495 cites W2058487877 @default.
• W4385563495 cites W2089335658 @default.
• W4385563495 cites W2100867326 @default.
• W4385563495 cites W2111326065 @default.
• W4385563495 cites W2116623522 @default.
• W4385563495 cites W2117750093 @default.
• W4385563495 cites W2119013806 @default.
• W4385563495 cites W2122732537 @default.
• W4385563495 cites W2129853470 @default.
• W4385563495 cites W2130395310 @default.
• W4385563495 cites W2141014201 @default.
• W4385563495 cites W2169243280 @default.
• W4385563495 cites W2170904281 @default.
• W4385563495 cites W2195303995 @default.
• W4385563495 cites W2419225477 @default.
• W4385563495 cites W2466594255 @default.
• W4385563495 cites W2535426958 @default.
• W4385563495 cites W2583025663 @default.
• W4385563495 cites W2609082695 @default.
• W4385563495 cites W2765121280 @default.
• W4385563495 cites W2766313490 @default.
• W4385563495 cites W2770026599 @default.
• W4385563495 cites W2949250633 @default.
• W4385563495 cites W3005432465 @default.
• W4385563495 cites W3023042104 @default.
• W4385563495 cites W3023683757 @default.
• W4385563495 cites W3095583226 @default.
• W4385563495 cites W3097920362 @default.
• W4385563495 cites W3104285666 @default.
• W4385563495 cites W3107322429 @default.
• W4385563495 cites W3112376646 @default.
• W4385563495 cites W3120428435 @default.
• W4385563495 cites W3123287010 @default.
• W4385563495 cites W3133491894 @default.
• W4385563495 cites W3177622815 @default.
• W4385563495 cites W4327573630 @default.
• W4385563495 doi "https://doi.org/10.1093/bioinformatics/btad484" @default.
• W4385563495 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37535750" @default.
• W4385563495 hasPublicationYear "2023" @default.
• W4385563495 type Work @default.
• W4385563495 citedByCount "1" @default.
• W4385563495 countsByYear W43855634952023 @default.
• W4385563495 crossrefType "journal-article" @default.
• W4385563495 hasAuthorship W4385563495A5017099204 @default.
• W4385563495 hasAuthorship W4385563495A5027499841 @default.
• W4385563495 hasAuthorship W4385563495A5050528382 @default.
• W4385563495 hasAuthorship W4385563495A5065866115 @default.
• W4385563495 hasBestOaLocation W43855634951 @default.
• W4385563495 hasConcept C107673813 @default.
• W4385563495 hasConcept C119857082 @default.
• W4385563495 hasConcept C12267149 @default.
• W4385563495 hasConcept C154945302 @default.
• W4385563495 hasConcept C199360897 @default.
• W4385563495 hasConcept C207201462 @default.
• W4385563495 hasConcept C41008148 @default.
• W4385563495 hasConcept C43126263 @default.
• W4385563495 hasConcept C515207424 @default.
• W4385563495 hasConcept C519991488 @default.
• W4385563495 hasConcept C52001869 @default.
• W4385563495 hasConcept C54355233 @default.
• W4385563495 hasConcept C60644358 @default.
• W4385563495 hasConcept C64502627 @default.
• W4385563495 hasConcept C68762167 @default.
• W4385563495 hasConcept C70721500 @default.
• W4385563495 hasConcept C86803240 @default.
• W4385563495 hasConcept C89423630 @default.
• W4385563495 hasConceptScore W4385563495C107673813 @default.
• W4385563495 hasConceptScore W4385563495C119857082 @default.
• W4385563495 hasConceptScore W4385563495C12267149 @default.
• W4385563495 hasConceptScore W4385563495C154945302 @default.
• W4385563495 hasConceptScore W4385563495C199360897 @default.
• W4385563495 hasConceptScore W4385563495C207201462 @default.
• W4385563495 hasConceptScore W4385563495C41008148 @default.
• W4385563495 hasConceptScore W4385563495C43126263 @default.
• W4385563495 hasConceptScore W4385563495C515207424 @default.
• W4385563495 hasConceptScore W4385563495C519991488 @default.
• W4385563495 hasConceptScore W4385563495C52001869 @default.
• W4385563495 hasConceptScore W4385563495C54355233 @default.
• W4385563495 hasConceptScore W4385563495C60644358 @default.
• W4385563495 hasConceptScore W4385563495C64502627 @default.
• W4385563495 hasConceptScore W4385563495C68762167 @default.
• W4385563495 hasConceptScore W4385563495C70721500 @default.
• W4385563495 hasConceptScore W4385563495C86803240 @default.
• W4385563495 hasConceptScore W4385563495C89423630 @default.
• W4385563495 hasFunder F4320327494 @default.

• next