To support semantic inter-operability between the biomedical information systems, it is necessary to determine the correspondences between the heterogeneous biomedical concepts, which is commonly known as biomedical o...To support semantic inter-operability between the biomedical information systems, it is necessary to determine the correspondences between the heterogeneous biomedical concepts, which is commonly known as biomedical ontology matching. Biomedical concepts are usually complex and ambiguous, which makes matching biomedical ontologies a challenge. Since none of the similarity measures can distinguish the heterogeneous biomedical concepts in any context independently, usually several similarity measures are applied together to determine the biomedical concepts mappings. However, the ignorance of the effects brought about by different biomedical concept mapping’s preference on the similarity measures significantly reduces the alignment’s quality. In this study, a non-dominated sorting genetic algorithm (NSGA)-III-based biomedical ontology matching technique is proposed to effectively match the biomedical ontologies, which first utilises an ontology partitioning technique to transform the large-scale biomedical ontology matching problem into several ontology segment-matching problems, and then uses NSGA-III to determine the optimal alignment without tuning the aggregating weights. The experiment is conducted on the anatomy track and large biomedic ontologies track which are provided by the Ontology Alignment Evaluation Initiative (OAEI), and the comparisons with OAEI’s participants show the effectiveness of the authors’ approach.展开更多
Dual labeling of an RNA can provide Förster resonance energy transfer(FRET)sensors for studying RNA folding,miRNA maturation,and RNA-protein interactions.Here,we report the development of a highly efficient strat...Dual labeling of an RNA can provide Förster resonance energy transfer(FRET)sensors for studying RNA folding,miRNA maturation,and RNA-protein interactions.Here,we report the development of a highly efficient strategy for direct dual-terminal labeling of any RNA of interest.We explored new Michael cycloaddition for facile labeling of 5′-terminal RNA with improved efficiency.Direct chemical tetrazinylation of RNA at the 3′-terminus was achieved with the highly efficient and catalysis-free tetrazine-cycloalkyne ligation.Both single-terminal labeling methods were combined for dual-terminal labeling of an RNA including short hairpin RNA,pre-miRNA,riboswitch,and noncoding RNA.Notably,these dual-labeled RNA-based FRET sensors were used to monitor RNA-ligand interactions in vitro and in live cells.It is anticipated that these universal RNA labeling strategies will be useful to study RNA structures and functions.展开更多
基金supported by the National Natural Science Foundation of China (Nos.61503082 and 61403121)the Natural Science Foundation of Fujian Province (No. 2016J05145)+3 种基金the Fundamental Research Funds for the Central Universities (No. 2015B20214)the Program for New Century Excellent Talents in Fujian Province University (No. GY-Z18155)the Program for Outstanding Young Scientific Researcher in Fujian Province University (No. GY-Z160149)the Scientific Research Foundation of Fujian University of Technology (No. GY-Z17162).
文摘To support semantic inter-operability between the biomedical information systems, it is necessary to determine the correspondences between the heterogeneous biomedical concepts, which is commonly known as biomedical ontology matching. Biomedical concepts are usually complex and ambiguous, which makes matching biomedical ontologies a challenge. Since none of the similarity measures can distinguish the heterogeneous biomedical concepts in any context independently, usually several similarity measures are applied together to determine the biomedical concepts mappings. However, the ignorance of the effects brought about by different biomedical concept mapping’s preference on the similarity measures significantly reduces the alignment’s quality. In this study, a non-dominated sorting genetic algorithm (NSGA)-III-based biomedical ontology matching technique is proposed to effectively match the biomedical ontologies, which first utilises an ontology partitioning technique to transform the large-scale biomedical ontology matching problem into several ontology segment-matching problems, and then uses NSGA-III to determine the optimal alignment without tuning the aggregating weights. The experiment is conducted on the anatomy track and large biomedic ontologies track which are provided by the Ontology Alignment Evaluation Initiative (OAEI), and the comparisons with OAEI’s participants show the effectiveness of the authors’ approach.
基金This research was made possible as a result of a generous grant from the National Nature Science Foundation of China(grant nos.21877008,32070670,and 22177010)the Zhejiang Provincial Natural Science Foundation of China(grant no.LY21C060003).
文摘Dual labeling of an RNA can provide Förster resonance energy transfer(FRET)sensors for studying RNA folding,miRNA maturation,and RNA-protein interactions.Here,we report the development of a highly efficient strategy for direct dual-terminal labeling of any RNA of interest.We explored new Michael cycloaddition for facile labeling of 5′-terminal RNA with improved efficiency.Direct chemical tetrazinylation of RNA at the 3′-terminus was achieved with the highly efficient and catalysis-free tetrazine-cycloalkyne ligation.Both single-terminal labeling methods were combined for dual-terminal labeling of an RNA including short hairpin RNA,pre-miRNA,riboswitch,and noncoding RNA.Notably,these dual-labeled RNA-based FRET sensors were used to monitor RNA-ligand interactions in vitro and in live cells.It is anticipated that these universal RNA labeling strategies will be useful to study RNA structures and functions.
