It is known that the localized surface plasmon resonance(LSPR) wavelength of plasmonics is highly dependent on compositions and geometry of plasmonics as well as the surrounding environments. Here, monodispersed Au@Ag...It is known that the localized surface plasmon resonance(LSPR) wavelength of plasmonics is highly dependent on compositions and geometry of plasmonics as well as the surrounding environments. Here, monodispersed Au@Ag core-shell nanoparticles(Au@Ag NPs) were prepared by carefully optimizing the shell thickness of Au@Ag NPs, and the presence of hydrogen sulfide(H_2 S) would significantly alter the LSPR wavelength. On the basis of this, a photothermal paper sensor for on-site recognition of H_2 S was constructed with a visual detection limit of 12.8 ng/L.展开更多
Transcriptome reconstruction is an important application of RNA-Seq,providing critical information for further analysis of transcriptome.Although RNA-Seq offers the potential to identify the whole picture of transcrip...Transcriptome reconstruction is an important application of RNA-Seq,providing critical information for further analysis of transcriptome.Although RNA-Seq offers the potential to identify the whole picture of transcriptome,it still presents special challenges.To handle these difficulties and reconstruct transcriptome as completely as possible,current computational approaches mainly employ two strategies:de novo assembly and genome-guided assembly.In order to find the similarities and differences between them,we firstly chose five representative assemblers belonging to the two classes respectively,and then investigated and compared their algorithm features in theory and real performances in practice.We found that all the methods can be reduced to graph reduction problems,yet they have different conceptual and practical implementations,thus each assembly method has its specific advantages and disadvantages,performing worse than others in certain aspects while outperforming others in anther aspects at the same time.Finally we merged assemblies of the five assemblers and obtained a much better assembly.Additionally we evaluated an assembler using genome-guided de novo assembly approach,and achieved good performance.Based on these results,we suggest that to obtain a comprehensive set of recovered transcripts,it is better to use a combination of de novo assembly and genome-guided assembly.展开更多
基金supported by the National Natural Science Foundation of China(21725501,21475007,21675009,21505003)the Fundamental Research Funds for the Central Universities(buctrc201706,buctrc201720)
文摘It is known that the localized surface plasmon resonance(LSPR) wavelength of plasmonics is highly dependent on compositions and geometry of plasmonics as well as the surrounding environments. Here, monodispersed Au@Ag core-shell nanoparticles(Au@Ag NPs) were prepared by carefully optimizing the shell thickness of Au@Ag NPs, and the presence of hydrogen sulfide(H_2 S) would significantly alter the LSPR wavelength. On the basis of this, a photothermal paper sensor for on-site recognition of H_2 S was constructed with a visual detection limit of 12.8 ng/L.
基金supported by the National Basic Research Program of China (2010CB945401)the National Natural Science Foundation of China (31240038, 31171264, 31071162, 31000590)the Science and Technology Commission of Shanghai Municipality (11DZ2260300)
文摘Transcriptome reconstruction is an important application of RNA-Seq,providing critical information for further analysis of transcriptome.Although RNA-Seq offers the potential to identify the whole picture of transcriptome,it still presents special challenges.To handle these difficulties and reconstruct transcriptome as completely as possible,current computational approaches mainly employ two strategies:de novo assembly and genome-guided assembly.In order to find the similarities and differences between them,we firstly chose five representative assemblers belonging to the two classes respectively,and then investigated and compared their algorithm features in theory and real performances in practice.We found that all the methods can be reduced to graph reduction problems,yet they have different conceptual and practical implementations,thus each assembly method has its specific advantages and disadvantages,performing worse than others in certain aspects while outperforming others in anther aspects at the same time.Finally we merged assemblies of the five assemblers and obtained a much better assembly.Additionally we evaluated an assembler using genome-guided de novo assembly approach,and achieved good performance.Based on these results,we suggest that to obtain a comprehensive set of recovered transcripts,it is better to use a combination of de novo assembly and genome-guided assembly.
