Prediction of the Number of Activated Genes in Multiple Independent Cd+2- and As+3-Induced Malignant Transformations of Human Urothelial Cells (UROtsa)
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{"title"=>"Prediction of the number of activated genes in multiple independent Cd +2- And As+3-induced malignant transformations of human urothelial cells (UROtsa)", "type"=>"journal", "authors"=>[{"first_name"=>"Scott H.", "last_name"=>"Garrett", "scopus_author_id"=>"7102507126"}, {"first_name"=>"Seema", "last_name"=>"Somji", "scopus_author_id"=>"6701679807"}, {"first_name"=>"Donald A.", "last_name"=>"Sens", "scopus_author_id"=>"7004442714"}, {"first_name"=>"Ke K.", "last_name"=>"Zhang", "scopus_author_id"=>"55570397300"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "sgr"=>"84899835144", "scopus"=>"2-s2.0-84899835144", "pui"=>"373020760", "doi"=>"10.1371/journal.pone.0085614", "pmid"=>"24465620"}, "id"=>"0ccdd8c0-e88c-327c-b2b2-8e97b9bc7eab", "abstract"=>"BACKGROUND: Many toxic environmental agents such as cadmium and arsenic are found to be epidemiologically linked to increasing rates of cancers. In vitro studies show that these toxic agents induced malignant transformation in human cells. It is not clear whether such malignant transformation induced by a single toxic agent is driven by a common set of genes. Although the advancement of high-throughput technology has facilitated the profiling of global gene expression, it remains a question whether the sample size is sufficient to identify this common driver gene set. RESULTS: We have developed a statistical method, SOFLR, to predict the number of common activated genes using a limited number of microarray samples. We conducted two case studies, cadmium and arsenic transformed human urothelial cells. Our method is able to precisely predict the number of stably induced and repressed genes and the number of samples to identify the common activated genes. The number of independent transformed isolates required for identifying the common activated genes is also estimated. The simulation study further validated our method and identified the important parameters in this analysis. CONCLUSIONS: Our method predicts the degree of similarity and diversity during cell malignant transformation by a single toxic agent. The results of our case studies imply the existence of common driver and passenger gene sets in toxin-induced transformation. Using a pilot study with small sample size, this method also helps microarray experimental design by determining the number of samples required to identify the common activated gene set.", "link"=>"http://www.mendeley.com/research/prediction-number-activated-genes-multiple-independent-cd-2-as3induced-malignant-transformations-hum", "reader_count"=>6, "reader_count_by_academic_status"=>{"Student > Ph. D. Student"=>1, "Student > Postgraduate"=>2, "Student > Master"=>1, "Student > Bachelor"=>1, "Unspecified"=>1}, "reader_count_by_user_role"=>{"Student > Ph. D. Student"=>1, "Student > Postgraduate"=>2, "Student > Master"=>1, "Student > Bachelor"=>1, "Unspecified"=>1}, "reader_count_by_subject_area"=>{"Biochemistry, Genetics and Molecular Biology"=>3, "Agricultural and Biological Sciences"=>1, "Neuroscience"=>1, "Unspecified"=>1}, "reader_count_by_subdiscipline"=>{"Neuroscience"=>{"Neuroscience"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>3}, "Unspecified"=>{"Unspecified"=>1}}, "reader_count_by_country"=>{"United States"=>1}, "group_count"=>0}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1355730", "https://ndownloader.figshare.com/files/1355731", "https://ndownloader.figshare.com/files/1355732", "https://ndownloader.figshare.com/files/1355733"], "description"=>"<div><p>Background</p><p>Many toxic environmental agents such as cadmium and arsenic are found to be epidemiologically linked to increasing rates of cancers. In vitro studies show that these toxic agents induced malignant transformation in human cells. It is not clear whether such malignant transformation induced by a single toxic agent is driven by a common set of genes. Although the advancement of high-throughput technology has facilitated the profiling of global gene expression, it remains a question whether the sample size is sufficient to identify this common driver gene set.</p><p>Results</p><p>We have developed a statistical method, SOFLR, to predict the number of common activated genes using a limited number of microarray samples. We conducted two case studies, cadmium and arsenic transformed human urothelial cells. Our method is able to precisely predict the number of stably induced and repressed genes and the number of samples to identify the common activated genes. The number of independent transformed isolates required for identifying the common activated genes is also estimated. The simulation study further validated our method and identified the important parameters in this analysis.</p><p>Conclusions</p><p>Our method predicts the degree of similarity and diversity during cell malignant transformation by a single toxic agent. The results of our case studies imply the existence of common driver and passenger gene sets in toxin-induced transformation. Using a pilot study with small sample size, this method also helps microarray experimental design by determining the number of samples required to identify the common activated gene set.</p></div>", "links"=>[], "tags"=>["Computational biology", "genomics", "Genome expression analysis", "microarrays", "toxicology", "Genetic toxicology", "Toxic agents", "Applied mathematics", "algorithms", "statistics", "Biostatistics", "Statistical methods", "activated", "genes", "malignant", "transformations", "urothelial", "cells"], "article_id"=>908201, "categories"=>["Biological Sciences", "Mathematics"], "users"=>["Scott H. Garrett", "Seema Somji", "Donald A. Sens", "Ke K. Zhang"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0085614.s001", "https://dx.doi.org/10.1371/journal.pone.0085614.s002", "https://dx.doi.org/10.1371/journal.pone.0085614.s003", "https://dx.doi.org/10.1371/journal.pone.0085614.s004"], "stats"=>{"downloads"=>5, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Prediction_of_the_Number_of_Activated_Genes_in_Multiple_Independent_Cd_2_and_As_3_Induced_Malignant_Transformations_of_Human_Urothelial_Cells_UROtsa_/908201", "title"=>"Prediction of the Number of Activated Genes in Multiple Independent Cd<sup>+2</sup>- and As<sup>+3</sup>-Induced Malignant Transformations of Human Urothelial Cells (UROtsa)", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-01-22 03:20:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355728"], "description"=>"<p>The x axis is the total number of genes in the passenger set, and the y axis is the number of isolates required for identifying a stable set of altered genes. The error bars show the standard errors for 10 replicates.</p>", "links"=>[], "tags"=>["Computational biology", "genomics", "Genome expression analysis", "microarrays", "toxicology", "Genetic toxicology", "Toxic agents", "Applied mathematics", "algorithms", "statistics", "Biostatistics", "Statistical methods"], "article_id"=>908199, "categories"=>["Biological Sciences", "Mathematics"], "users"=>["Scott H. Garrett", "Seema Somji", "Donald A. Sens", "Ke K. Zhang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085614.g005", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Simulation_analysis_for_the_minimum_number_of_isolates_/908199", "title"=>"Simulation analysis for the minimum number of isolates.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-22 03:20:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355729"], "description"=>"<p>Microarray validation using a customized qPCR array.</p>", "links"=>[], "tags"=>["Computational biology", "genomics", "Genome expression analysis", "microarrays", "toxicology", "Genetic toxicology", "Toxic agents", "Applied mathematics", "algorithms", "statistics", "Biostatistics", "Statistical methods", "validation", "customized", "qpcr"], "article_id"=>908200, "categories"=>["Biological Sciences", "Mathematics"], "users"=>["Scott H. Garrett", "Seema Somji", "Donald A. Sens", "Ke K. Zhang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085614.t001", "stats"=>{"downloads"=>3, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Microarray_validation_using_a_customized_qPCR_array_/908200", "title"=>"Microarray validation using a customized qPCR array.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-01-22 03:20:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355727"], "description"=>"<p>The x axis is the number of isolates, n.isolates, and the y-axis is the number of overlapping probes in original scale or in logarithm scale. <b>A</b> and <b>C</b>: 4P logistic curve fitting for the overlapping probes. <b>B</b> and <b>D</b>: the optimal linear fitting for the overlapping probes at logarithm scale.</p>", "links"=>[], "tags"=>["Computational biology", "genomics", "Genome expression analysis", "microarrays", "toxicology", "Genetic toxicology", "Toxic agents", "Applied mathematics", "algorithms", "statistics", "Biostatistics", "Statistical methods", "fitting", "overlapping", "probes", "transformed"], "article_id"=>908198, "categories"=>["Biological Sciences", "Mathematics"], "users"=>["Scott H. Garrett", "Seema Somji", "Donald A. Sens", "Ke K. Zhang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085614.g004", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_fitting_of_the_number_of_overlapping_probes_for_As_2_transformed_cells_/908198", "title"=>"Model fitting of the number of overlapping probes for As<sup>+2</sup> transformed cells.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-22 03:20:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355724"], "description"=>"<p>The heat map of all UROtsa As<sup>+3</sup> and Cd<sup>+2</sup> transformed isolates with the non-transformed parental controls in comparison to that of As<sup>+3</sup> transformed UROtsa cells. The map consists of 4,454 probes that exhibited the greatest variation in expression across isolates. The non-transformed controls and transformed isolates formed three distinct groups by hierarchical clustering.</p>", "links"=>[], "tags"=>["Computational biology", "genomics", "Genome expression analysis", "microarrays", "toxicology", "Genetic toxicology", "Toxic agents", "Applied mathematics", "algorithms", "statistics", "Biostatistics", "Statistical methods"], "article_id"=>908195, "categories"=>["Biological Sciences", "Mathematics"], "users"=>["Scott H. Garrett", "Seema Somji", "Donald A. Sens", "Ke K. Zhang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085614.g001", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Heat_map_/908195", "title"=>"Heat map.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-22 03:20:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355726"], "description"=>"<p>The x axis is the number of isolates, n.isolates, and the y-axis is the number of overlapping probes in original scale or in logarithm scale. <b>A</b> and <b>C</b>: 4P logistic curve fitting for the overlapping probes. <b>B</b> and <b>D</b>: the optimal linear fitting for the overlapping probes at logarithm scale.</p>", "links"=>[], "tags"=>["Computational biology", "genomics", "Genome expression analysis", "microarrays", "toxicology", "Genetic toxicology", "Toxic agents", "Applied mathematics", "algorithms", "statistics", "Biostatistics", "Statistical methods", "fitting", "overlapping", "probes", "transformed"], "article_id"=>908197, "categories"=>["Biological Sciences", "Mathematics"], "users"=>["Scott H. Garrett", "Seema Somji", "Donald A. Sens", "Ke K. Zhang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085614.g003", "stats"=>{"downloads"=>2, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_fitting_of_the_number_of_overlapping_probes_for_Cd_2_transformed_cells_/908197", "title"=>"Model fitting of the number of overlapping probes for Cd<sup>+2</sup> transformed cells.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-22 03:20:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355725"], "description"=>"<p>The Venn diagram depicts the number of Affymetrix 133 Plus 2.0 array probes that exhibit a two-fold change in gene expression in each metal-transformed UROtsa isolate compared to non-transformed UROtsa cells. The transformed isolate number is also depicted within each oval in red, and the probe overlap (number of probes expressed in all isolates) is shown in the middle of each rosette.</p>", "links"=>[], "tags"=>["Computational biology", "genomics", "Genome expression analysis", "microarrays", "toxicology", "Genetic toxicology", "Toxic agents", "Applied mathematics", "algorithms", "statistics", "Biostatistics", "Statistical methods", "diagram", "transformed", "urotsa"], "article_id"=>908196, "categories"=>["Biological Sciences", "Mathematics"], "users"=>["Scott H. Garrett", "Seema Somji", "Donald A. Sens", "Ke K. Zhang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085614.g002", "stats"=>{"downloads"=>0, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Venn_diagram_for_the_number_of_gene_expression_changes_in_metal_transformed_UROtsa_cells_/908196", "title"=>"Venn diagram for the number of gene expression changes in metal transformed UROtsa cells.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-22 03:20:29"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"12", "full-text"=>"8", "pdf"=>"4", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2014", "month"=>"2"}
  • {"unique-ip"=>"11", "full-text"=>"13", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"3"}
  • {"unique-ip"=>"6", "full-text"=>"5", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"5"}
  • {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"6"}
  • {"unique-ip"=>"15", "full-text"=>"14", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"5", "cited-by"=>"0", "year"=>"2014", "month"=>"4"}
  • {"unique-ip"=>"7", "full-text"=>"6", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"4"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"5"}
  • {"unique-ip"=>"6", "full-text"=>"8", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2015", "month"=>"6"}
  • {"unique-ip"=>"2", "full-text"=>"4", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"4", "cited-by"=>"1", "year"=>"2015", "month"=>"7"}
  • {"unique-ip"=>"5", "full-text"=>"4", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"3"}
  • {"unique-ip"=>"2", "full-text"=>"1", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"2"}
  • {"unique-ip"=>"8", "full-text"=>"7", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"5", "cited-by"=>"0", "year"=>"2015", "month"=>"8"}
  • {"unique-ip"=>"8", "full-text"=>"7", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"9"}
  • {"unique-ip"=>"4", "full-text"=>"6", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"10"}
  • {"unique-ip"=>"7", "full-text"=>"6", "pdf"=>"2", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"7"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2014", "month"=>"8"}
  • {"unique-ip"=>"7", "full-text"=>"3", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2014", "month"=>"9"}
  • {"unique-ip"=>"8", "full-text"=>"6", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2014", "month"=>"10"}
  • {"unique-ip"=>"5", "full-text"=>"7", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2016", "month"=>"2"}
  • {"unique-ip"=>"4", "full-text"=>"2", "pdf"=>"1", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"11"}
  • {"unique-ip"=>"5", "full-text"=>"4", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"12"}
  • {"unique-ip"=>"5", "full-text"=>"3", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"1"}
  • {"unique-ip"=>"10", "full-text"=>"8", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2015", "month"=>"11"}
  • {"unique-ip"=>"11", "full-text"=>"8", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2015", "month"=>"12"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"1"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"3"}
  • {"unique-ip"=>"3", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"4"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"5"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"8", "cited-by"=>"0", "year"=>"2016", "month"=>"6"}
  • {"unique-ip"=>"5", "full-text"=>"3", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"7"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"8"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"9"}
  • {"unique-ip"=>"3", "full-text"=>"2", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2016", "month"=>"11"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"12"}
  • {"unique-ip"=>"3", "full-text"=>"6", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"1"}
  • {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"2"}
  • {"unique-ip"=>"2", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"7", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"3"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"4"}
  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"5"}
  • {"unique-ip"=>"2", "full-text"=>"0", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"7"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"8"}
  • {"unique-ip"=>"7", "full-text"=>"3", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"1", "year"=>"2017", "month"=>"9"}
  • {"unique-ip"=>"3", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"10"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"11"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"1"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"2"}
  • {"unique-ip"=>"1", "full-text"=>"0", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"1"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
  • {"unique-ip"=>"9", "full-text"=>"7", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"7", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"6", "full-text"=>"5", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"2", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"3", "full-text"=>"4", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}
  • {"unique-ip"=>"6", "full-text"=>"7", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}
  • {"unique-ip"=>"9", "full-text"=>"11", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"10"}

Relative Metric

{"start_date"=>"2014-01-01T00:00:00Z", "end_date"=>"2014-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences/Toxicology", "average_usage"=>[266, 408]}, {"subject_area"=>"/Medicine and health sciences", "average_usage"=>[285]}, {"subject_area"=>"/Medicine and health sciences/Oncology", "average_usage"=>[266]}, {"subject_area"=>"/Physical sciences/Mathematics", "average_usage"=>[286]}]}
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