{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Chen JQ"],"funding":["National Key R&D Program of China"],"pagination":["50"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9040240"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["17(1)"],"pubmed_abstract":["<h4>Background</h4>Rhei Radix et Rhizoma (rhubarb), as one of the typical representatives of multi-effect traditional Chinese medicines (TCMs), has been utilized in the treatment of various diseases due to its multicomponent nature. However, there are few systematic investigations for the corresponding effect of individual components in rhubarb. Hence, we aimed to develop a novel strategy to fuzzily identify bioactive components for different efficacies of rhubarb by the back propagation (BP) neural network association analysis of ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry for every data (UPLC-Q-TOF/MS<sup>E</sup>) and integrated effects.<h4>Methods</h4>Through applying the fuzzy chemical identification, most components of rhubarb were classified in"],"journal":["Chinese medicine"],"pubmed_title":["Fuzzy identification of bioactive components for different efficacies of rhubarb by the back propagation neural network association analysis of UPLC-Q-TOF/MS<sup>E</sup> and integrated effects."],"pmcid":["PMC9040240"],"funding_grant_id":["2019YFC1711000"],"pubmed_authors":["Tao HJ","Yue SJ","Duan JA","Chen JQ","Zhou GS","Shang EX","Pu ZJ","Chen YY","Du X","Shi XQ","Tang YP"],"additional_accession":[]},"is_claimable":false,"name":"Fuzzy identification of bioactive components for different efficacies of rhubarb by the back propagation neural network association analysis of UPLC-Q-TOF/MS<sup>E</sup> and integrated effects.","description":"<h4>Background</h4>Rhei Radix et Rhizoma (rhubarb), as one of the typical representatives of multi-effect traditional Chinese medicines (TCMs), has been utilized in the treatment of various diseases due to its multicomponent nature. However, there are few systematic investigations for the corresponding effect of individual components in rhubarb. Hence, we aimed to develop a novel strategy to fuzzily identify bioactive components for different efficacies of rhubarb by the back propagation (BP) neural network association analysis of ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry for every data (UPLC-Q-TOF/MS<sup>E</sup>) and integrated effects.<h4>Methods</h4>Through applying the fuzzy chemical identification, most components of rhubarb were classified in","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Apr","modification":"2025-04-22T07:47:25.5Z","creation":"2025-02-19T03:47:24.044Z"},"accession":"S-EPMC9040240","cross_references":{"pubmed":["35473719"],"doi":["10.1186/s13020-022-00612-9"]}}