Matches in SemOpenAlex for { <https://semopenalex.org/work/W2623058021> ?p ?o ?g. }
Showing items 1 to 90 of
90
with 100 items per page.
- W2623058021 endingPage "228" @default.
- W2623058021 startingPage "222" @default.
- W2623058021 abstract "Human metabolomics has great potential in disease mechanism understanding, early diagnosis, and therapy. Existing metabolomics studies are often based on profiling patient biofluids and tissue samples and are difficult owing to the challenges of sample collection and data processing. Here, we report an alternative approach and developed a computation-based prediction system, MetabolitePredict, for disease metabolomics biomarker prediction. We applied MetabolitePredict to identify metabolite biomarkers and metabolite targeting therapies for rheumatoid arthritis (RA), a last-lasting complex disease with multiple genetic and environmental factors involved. MetabolitePredict is a de novo prediction system. It first constructs a disease-specific genetic profile using genes and pathways data associated with an input disease. It then constructs genetic profiles for a total of 259,170 chemicals/metabolites using known chemical genetics and human metabolomic data. MetabolitePredict prioritizes metabolites for a given disease based on the genetic profile similarities between disease and metabolites. We evaluated MetabolitePredict using 63 known RA-associated metabolites. MetabolitePredict found 24 of the 63 metabolites (recall: 0.38) and ranked them highly (mean ranking: top 4.13%, median ranking: top 1.10%, P-value: 5.08E−19). MetabolitePredict performed better than an existing metabolite prediction system, PROFANCY, in predicting RA-associated metabolites (PROFANCY: recall: 0.31, mean ranking: 20.91%, median ranking: 16.47%, P-value: 3.78E−7). Short-chain fatty acids (SCFAs), the abundant metabolites of gut microbiota in the fermentation of fiber, ranked highly (butyrate, 0.03%; acetate, 0.05%; propionate, 0.38%). Finally, we established MetabolitePredict’s potential in novel metabolite targeting for disease treatment: MetabolitePredict ranked highly three known metabolite inhibitors for RA treatments (methotrexate:0.25%; leflunomide: 0.56%; sulfasalazine: 0.92%). MetabolitePredict is a generalizable disease metabolite prediction system. The only required input to the system is a disease name or a set of disease-associated genes. The web-based MetabolitePredict is available at:http://xulab.case.edu/MetabolitePredict." @default.
- W2623058021 created "2017-06-15" @default.
- W2623058021 creator A5050134236 @default.
- W2623058021 creator A5067895364 @default.
- W2623058021 date "2017-07-01" @default.
- W2623058021 modified "2023-10-16" @default.
- W2623058021 title "MetabolitePredict: A de novo human metabolomics prediction system and its applications in rheumatoid arthritis" @default.
- W2623058021 cites W1517711897 @default.
- W2623058021 cites W1966157956 @default.
- W2623058021 cites W1969889522 @default.
- W2623058021 cites W1978370150 @default.
- W2623058021 cites W1998695576 @default.
- W2623058021 cites W2004362888 @default.
- W2623058021 cites W2010457001 @default.
- W2623058021 cites W2012490955 @default.
- W2623058021 cites W2036618418 @default.
- W2623058021 cites W2054218135 @default.
- W2623058021 cites W2055280685 @default.
- W2623058021 cites W2062222093 @default.
- W2623058021 cites W2063028213 @default.
- W2623058021 cites W2092717823 @default.
- W2623058021 cites W2099752694 @default.
- W2623058021 cites W2110826367 @default.
- W2623058021 cites W2116868464 @default.
- W2623058021 cites W2119412782 @default.
- W2623058021 cites W2131058075 @default.
- W2623058021 cites W2131719921 @default.
- W2623058021 cites W2140603258 @default.
- W2623058021 cites W2149515881 @default.
- W2623058021 cites W2149952321 @default.
- W2623058021 cites W2165067288 @default.
- W2623058021 cites W2179544415 @default.
- W2623058021 cites W2292791349 @default.
- W2623058021 cites W2508485654 @default.
- W2623058021 doi "https://doi.org/10.1016/j.jbi.2017.06.002" @default.
- W2623058021 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5602605" @default.
- W2623058021 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28600026" @default.
- W2623058021 hasPublicationYear "2017" @default.
- W2623058021 type Work @default.
- W2623058021 sameAs 2623058021 @default.
- W2623058021 citedByCount "9" @default.
- W2623058021 countsByYear W26230580212018 @default.
- W2623058021 countsByYear W26230580212019 @default.
- W2623058021 countsByYear W26230580212020 @default.
- W2623058021 countsByYear W26230580212023 @default.
- W2623058021 crossrefType "journal-article" @default.
- W2623058021 hasAuthorship W2623058021A5050134236 @default.
- W2623058021 hasAuthorship W2623058021A5067895364 @default.
- W2623058021 hasBestOaLocation W26230580212 @default.
- W2623058021 hasConcept C126322002 @default.
- W2623058021 hasConcept C21565614 @default.
- W2623058021 hasConcept C2777477808 @default.
- W2623058021 hasConcept C2779134260 @default.
- W2623058021 hasConcept C2994400308 @default.
- W2623058021 hasConcept C60644358 @default.
- W2623058021 hasConcept C70721500 @default.
- W2623058021 hasConcept C71924100 @default.
- W2623058021 hasConcept C86803240 @default.
- W2623058021 hasConceptScore W2623058021C126322002 @default.
- W2623058021 hasConceptScore W2623058021C21565614 @default.
- W2623058021 hasConceptScore W2623058021C2777477808 @default.
- W2623058021 hasConceptScore W2623058021C2779134260 @default.
- W2623058021 hasConceptScore W2623058021C2994400308 @default.
- W2623058021 hasConceptScore W2623058021C60644358 @default.
- W2623058021 hasConceptScore W2623058021C70721500 @default.
- W2623058021 hasConceptScore W2623058021C71924100 @default.
- W2623058021 hasConceptScore W2623058021C86803240 @default.
- W2623058021 hasLocation W26230580211 @default.
- W2623058021 hasLocation W26230580212 @default.
- W2623058021 hasLocation W26230580213 @default.
- W2623058021 hasLocation W26230580214 @default.
- W2623058021 hasOpenAccess W2623058021 @default.
- W2623058021 hasPrimaryLocation W26230580211 @default.
- W2623058021 hasRelatedWork W1967527526 @default.
- W2623058021 hasRelatedWork W1978461542 @default.
- W2623058021 hasRelatedWork W2007897985 @default.
- W2623058021 hasRelatedWork W2043547988 @default.
- W2623058021 hasRelatedWork W2209046906 @default.
- W2623058021 hasRelatedWork W2395698613 @default.
- W2623058021 hasRelatedWork W2970747969 @default.
- W2623058021 hasRelatedWork W2980667428 @default.
- W2623058021 hasRelatedWork W4285082252 @default.
- W2623058021 hasRelatedWork W97902761 @default.
- W2623058021 hasVolume "71" @default.
- W2623058021 isParatext "false" @default.
- W2623058021 isRetracted "false" @default.
- W2623058021 magId "2623058021" @default.
- W2623058021 workType "article" @default.