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    Additional file 4: of Silica diatom shells tailored with Au nanoparticles enable sensitive analysis of molecules for biological, safety and environment applications

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    Type
    Data File
    Authors
    Onesto, V.
    Villani, M.
    Coluccio, M. L.
    Majewska, R.
    Alabastri, A.
    Battista, E.
    Schirato, A.
    Calestani, D.
    Coppedé, N.
    Cesarelli, M.
    Amato, F.
    Di Fabrizio, Enzo M. cc
    Gentile, F.
    KAUST Department
    Physical Science and Engineering (PSE) Division
    Material Science and Engineering Program
    Date
    2018
    Permanent link to this record
    http://hdl.handle.net/10754/664068
    
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    Show full item record
    Abstract
    Supporting figures to the Numerical Simulation Methods of the main text. (DOCX 608Â kb)
    Citation
    V. Onesto, M. Villani, M. Coluccio, R. Majewska, A. Alabastri, E. Battista, A. Schirato, D. Calestani, N. CoppedĂŠ, M. Cesarelli, F. Amato, E. Di Fabrizio, & F. Gentile. (2018). Additional file 4: of Silica diatom shells tailored with Au nanoparticles enable sensitive analysis of molecules for biological, safety and environment applications. Figshare. https://doi.org/10.6084/M9.FIGSHARE.6119213
    Publisher
    figshare
    DOI
    10.6084/m9.figshare.6119213
    Relations
    Is Supplement To:
    • [Article]
      Onesto V, Villani M, Coluccio ML, Majewska R, Alabastri A, et al. (2018) Silica diatom shells tailored with Au nanoparticles enable sensitive analysis of molecules for biological, safety and environment applications. Nanoscale Research Letters 13. Available: http://dx.doi.org/10.1186/s11671-018-2507-4.. DOI: 10.1186/s11671-018-2507-4 HANDLE: 10754/627609
    ae974a485f413a2113503eed53cd6c53
    10.6084/m9.figshare.6119213
    Scopus Count
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    Physical Science and Engineering (PSE) Division; Material Science and Engineering Program; Datasets

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      Impact of data preprocessing on cell-type clustering based on single-cell RNA-seq data

      Wang, Chunxiang; Gao, Xin; Liu, Juntao (figshare, 2020) [Dataset]
      Abstract Background Advances in single-cell RNA-seq technology have led to great opportunities for the quantitative characterization of cell types, and many clustering algorithms have been developed based on single-cell gene expression. However, we found that different data preprocessing methods show quite different effects on clustering algorithms. Moreover, there is no specific preprocessing method that is applicable to all clustering algorithms, and even for the same clustering algorithm, the best preprocessing method depends on the input data. Results We designed a graph-based algorithm, SC3-e, specifically for discriminating the best data preprocessing method for SC3, which is currently the most widely used clustering algorithm for single cell clustering. When tested on eight frequently used single-cell RNA-seq data sets, SC3-e always accurately selects the best data preprocessing method for SC3 and therefore greatly enhances the clustering performance of SC3. Conclusion The SC3-e algorithm is practically powerful for discriminating the best data preprocessing method, and therefore largely enhances the performance of cell-type clustering of SC3. It is expected to play a crucial role in the related studies of single-cell clustering, such as the studies of human complex diseases and discoveries of new cell types.
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      Supplementary Material for: Global expression differences and tissue specific expression differences in rice evolution result in two contrasting types of differentially expressed genes

      Horiuchi, Youko; Harushima, Yoshiaki; Fujisawa, Hironori; Mochizuki, Takako; Fujita, Masahiro; Ohyanagi, Hajime; Kurata, Nori (figshare, 2015) [Dataset]
      Abstract Background Since the development of transcriptome analysis systems, many expression evolution studies characterized evolutionary forces acting on gene expression, without explicit discrimination between global expression differences and tissue specific expression differences. However, different types of gene expression alteration should have different effects on an organism, the evolutionary forces that act on them might be different, and different types of genes might show different types of differential expression between species. To confirm this, we studied differentially expressed (DE) genes among closely related groups that have extensive gene expression atlases, and clarified characteristics of different types of DE genes including the identification of regulating loci for differential expression using expression quantitative loci (eQTL) analysis data. Results We detected differentially expressed (DE) genes between rice subspecies in five homologous tissues that were verified using japonica and indica transcriptome atlases in public databases. Using the transcriptome atlases, we classified DE genes into two types, global DE genes and changed-tissues DE genes. Global type DE genes were not expressed in any tissues in the atlas of one subspecies, however changed-tissues type DE genes were expressed in both subspecies with different tissue specificity. For the five tissues in the two japonica-indica combinations, 4.6 ± 0.8 and 5.9 ± 1.5 % of highly expressed genes were global and changed-tissues DE genes, respectively. Changed-tissues DE genes varied in number between tissues, increasing linearly with the abundance of tissue specifically expressed genes in the tissue. Molecular evolution of global DE genes was rapid, unlike that of changed-tissues DE genes. Based on gene ontology, global and changed-tissues DE genes were different, having no common GO terms. Expression differences of most global DE genes were regulated by cis-eQTLs. Expression evolution of changed-tissues DE genes was rapid in tissue specifically expressed genes and those rapidly evolved changed-tissues DE genes were regulated not by cis-eQTLs, but by complicated trans-eQTLs. Conclusions Global DE genes and changed-tissues DE genes had contrasting characteristics. The two contrasting types of DE genes provide possible explanations for the previous controversial conclusions about the relationships between molecular evolution and expression evolution of genes in different species, and the relationship between expression breadth and expression conservation in evolution.
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      A transcriptional analysis of carotenoid, chlorophyll and plastidial isoprenoid biosynthesis genes during development and osmotic stress responses in Arabidopsis thaliana

      Meier, Stuart Kurt; Tzfadia, Oren; Vallabhaneni, Ratnakar; Gehring, Christoph A; Wurtzel, Eleanore T (BMC Systems Biology, Springer Nature, 2011-05-19) [Article]
      Background: The carotenoids are pure isoprenoids that are essential components of the photosynthetic apparatus and are coordinately synthesized with chlorophylls in chloroplasts. However, little is known about the mechanisms that regulate carotenoid biosynthesis or the mechanisms that coordinate this synthesis with that of chlorophylls and other plastidial synthesized isoprenoid-derived compounds, including quinones, gibberellic acid and abscisic acid. Here, a comprehensive transcriptional analysis of individual carotenoid and isoprenoid-related biosynthesis pathway genes was performed in order to elucidate the role of transcriptional regulation in the coordinated synthesis of these compounds and to identify regulatory components that may mediate this process in Arabidopsis thaliana.Results: A global microarray expression correlation analysis revealed that the phytoene synthase gene, which encodes the first dedicated and rate-limiting enzyme of carotenogenesis, is highly co-expressed with many photosynthesis-related genes including many isoprenoid-related biosynthesis pathway genes. Chemical and mutant analysis revealed that induction of the co-expressed genes following germination was dependent on gibberellic acid and brassinosteroids (BR) but was inhibited by abscisic acid (ABA). Mutant analyses further revealed that expression of many of the genes is suppressed in dark grown plants by Phytochrome Interacting transcription Factors (PIFs) and activated by photoactivated phytochromes, which in turn degrade PIFs and mediate a coordinated induction of the genes. The promoters of PSY and the co-expressed genes were found to contain an enrichment in putative BR-auxin response elements and G-boxes, which bind PIFs, further supporting a role for BRs and PIFs in regulating expression of the genes. In osmotically stressed root tissue, transcription of Calvin cycle, methylerythritol 4-phosphate pathway and carotenoid biosynthesis genes is induced and uncoupled from that of chlorophyll biosynthesis genes in a manner that is consistent with the increased synthesis of carotenoid precursors for ABA biosynthesis. In all tissues examined, induction of ?-carotene hydroxylase transcript levels are linked to an increased demand for ABA.Conclusions: This analysis provides compelling evidence to suggest that coordinated transcriptional regulation of isoprenoid-related biosynthesis pathway genes plays a major role in coordinating the synthesis of functionally related chloroplast localized isoprenoid-derived compounds. 2011 Meier et al; licensee BioMed Central Ltd.
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