Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture
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{"title"=>"Molecular predictors of 3D morphogenesis by breast cancer cell lines in 3D culture", "type"=>"journal", "authors"=>[{"first_name"=>"Ju", "last_name"=>"Han", "scopus_author_id"=>"8873057000"}, {"first_name"=>"Hang", "last_name"=>"Chang", "scopus_author_id"=>"23007709700"}, {"first_name"=>"Orsi", "last_name"=>"Giricz", "scopus_author_id"=>"36011831400"}, {"first_name"=>"Genee Y.", "last_name"=>"Lee", "scopus_author_id"=>"16301585300"}, {"first_name"=>"Frederick L.", "last_name"=>"Baehner", "scopus_author_id"=>"6506368913"}, {"first_name"=>"Joe W.", "last_name"=>"Gray", "scopus_author_id"=>"7404300313"}, {"first_name"=>"Mina J.", "last_name"=>"Bissell", "scopus_author_id"=>"7103410472"}, {"first_name"=>"Paraic A.", "last_name"=>"Kenny", "scopus_author_id"=>"7102145765"}, {"first_name"=>"Bahram", "last_name"=>"Parvin", "scopus_author_id"=>"7004401376"}], "year"=>2010, "source"=>"PLoS Computational Biology", "identifiers"=>{"isbn"=>"1553-7358", "pmid"=>"20195492", "doi"=>"10.1371/journal.pcbi.1000684", "pui"=>"358387518", "issn"=>"1553734X", "sgr"=>"77649220426", "scopus"=>"2-s2.0-77649220426"}, "id"=>"6541bd6d-a191-3653-b969-1881b0a9946e", "abstract"=>"Correlative analysis of molecular markers with phenotypic signatures is the simplest model for hypothesis generation. In this paper, a panel of 24 breast cell lines was grown in 3D culture, their morphology was imaged through phase contrast microscopy, and computational methods were developed to segment and represent each colony at multiple dimensions. Subsequently, subpopulations from these morphological responses were identified through consensus clustering to reveal three clusters of round, grape-like, and stellate phenotypes. In some cases, cell lines with particular pathobiological phenotypes clustered together (e.g., ERBB2 amplified cell lines sharing the same morphometric properties as the grape-like phenotype). Next, associations with molecular features were realized through (i) differential analysis within each morphological cluster, and (ii) regression analysis across the entire panel of cell lines. In both cases, the dominant genes that are predictive of the morphological signatures were identified. Specifically, PPARgamma has been associated with the invasive stellate morphological phenotype, which corresponds to triple-negative pathobiology. PPARgamma has been validated through two supporting biological assays.", "link"=>"http://www.mendeley.com/research/molecular-predictors-3d-morphogenesis-breast-cancer-cell-lines-3d-culture", "reader_count"=>104, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>4, "Researcher"=>27, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>31, "Student > Postgraduate"=>5, "Other"=>4, "Student > Master"=>8, "Student > Bachelor"=>8, "Lecturer"=>4, "Professor"=>5, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>4, "Researcher"=>27, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>31, "Student > Postgraduate"=>5, "Other"=>4, "Student > Master"=>8, "Student > Bachelor"=>8, "Lecturer"=>4, "Professor"=>5, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>6, "Unspecified"=>4, "Biochemistry, Genetics and Molecular Biology"=>20, "Nursing and Health Professions"=>1, "Materials Science"=>2, "Mathematics"=>1, "Medicine and Dentistry"=>8, "Agricultural and Biological Sciences"=>56, "Chemistry"=>4, "Social Sciences"=>1, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>6}, "Materials Science"=>{"Materials Science"=>2}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>8}, "Chemistry"=>{"Chemistry"=>4}, "Social Sciences"=>{"Social Sciences"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>56}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>20}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>4}}, "reader_count_by_country"=>{"United States"=>4, "United Kingdom"=>1, "South Africa"=>1, "France"=>1, "Portugal"=>1, "India"=>1}, "group_count"=>6}

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  • {"files"=>["https://ndownloader.figshare.com/files/860241"], "description"=>"<p>A darker block indicates higher morphological similarity between two cell lines. One can hypothesize that the larger block for has been partitioned into two blocks for ; however, the order is not preserved.</p>", "links"=>[], "tags"=>["matrices", "numbers", "clusters", "morphological", "representations"], "article_id"=>530688, "categories"=>["Information And Computing Sciences", "Molecular Biology", "Cell Biology", "Medicine"], "users"=>["Ju Han", "Hang Chang", "Orsi Giricz", "Genee Y. Lee", "Frederick L. Baehner", "Joe W. Gray", "Mina J. Bissell", "Paraic A. Kenny", "Bahram Parvin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000684.g002", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_consensus_matrices_for_different_numbers_of_clusters_based_on_morphological_representations_are_shown_/530688", "title"=>"The consensus matrices for different numbers of clusters based on morphological representations are shown.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-02-26 00:11:28"}
  • {"files"=>["https://ndownloader.figshare.com/files/427582"], "description"=>"<div><p>Correlative analysis of molecular markers with phenotypic signatures is the simplest model for hypothesis generation. In this paper, a panel of 24 breast cell lines was grown in 3D culture, their morphology was imaged through phase contrast microscopy, and computational methods were developed to segment and represent each colony at multiple dimensions. Subsequently, subpopulations from these morphological responses were identified through consensus clustering to reveal three clusters of round, grape-like, and stellate phenotypes. In some cases, cell lines with particular pathobiological phenotypes clustered together (e.g., ERBB2 amplified cell lines sharing the same morphometric properties as the grape-like phenotype). Next, associations with molecular features were realized through (i) differential analysis within each morphological cluster, and (ii) regression analysis across the entire panel of cell lines. In both cases, the dominant genes that are predictive of the morphological signatures were identified. Specifically, PPARγ has been associated with the invasive stellate morphological phenotype, which corresponds to triple-negative pathobiology. PPARγ has been validated through two supporting biological assays.</p></div>", "links"=>[], "tags"=>["molecular", "predictors", "3d", "morphogenesis", "cancer", "lines"], "article_id"=>144418, "categories"=>["Information And Computing Sciences", "Molecular Biology", "Cell Biology", "Medicine"], "users"=>["Ju Han", "Hang Chang", "Orsi Giricz", "Genee Y. Lee", "Frederick L. Baehner", "Joe W. Gray", "Mina J. Bissell", "Paraic A. Kenny", "Bahram Parvin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000684", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Molecular_Predictors_of_3D_Morphogenesis_by_Breast_Cancer_Cell_Lines_in_3D_Culture/144418", "title"=>"Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-02-26 01:13:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/861071"], "description"=>"<p>Genes that best predict the size of the colony in terms of negative logistic relationship ().</p>", "links"=>[], "tags"=>["logistic"], "article_id"=>531524, "categories"=>["Information And Computing Sciences", "Molecular Biology", "Cell Biology", "Medicine"], "users"=>["Ju Han", "Hang Chang", "Orsi Giricz", "Genee Y. Lee", "Frederick L. Baehner", "Joe W. Gray", "Mina J. Bissell", "Paraic A. Kenny", "Bahram Parvin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000684.t003", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Genes_that_best_predict_the_size_of_the_colony_in_terms_of_negative_logistic_relationship_/531524", "title"=>"Genes that best predict the size of the colony in terms of negative logistic relationship ().", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-02-26 00:25:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/861105"], "description"=>"<p>Genes that best predict the size of the colony in terms of positive logistic relationship ().</p>", "links"=>[], "tags"=>["logistic"], "article_id"=>531558, "categories"=>["Information And Computing Sciences", "Molecular Biology", "Cell Biology", "Medicine"], "users"=>["Ju Han", "Hang Chang", "Orsi Giricz", "Genee Y. Lee", "Frederick L. Baehner", "Joe W. Gray", "Mina J. Bissell", "Paraic A. Kenny", "Bahram Parvin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000684.t002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Genes_that_best_predict_the_size_of_the_colony_in_terms_of_positive_logistic_relationship_/531558", "title"=>"Genes that best predict the size of the colony in terms of positive logistic relationship ().", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-02-26 00:25:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/860634"], "description"=>"<p>(A) untreated line, (B) treatment with Gw-9662, and (C) proliferation index. The proliferation index was determined by incubating cultures with cell proliferation analysis reagent, WST1, on Day 5.</p>", "links"=>[], "tags"=>["mda-mb-231", "pparg-inhibitor", "indicates", "proliferation"], "article_id"=>531080, "categories"=>["Information And Computing Sciences", "Molecular Biology", "Cell Biology", "Medicine"], "users"=>["Ju Han", "Hang Chang", "Orsi Giricz", "Genee Y. Lee", "Frederick L. Baehner", "Joe W. Gray", "Mina J. Bissell", "Paraic A. Kenny", "Bahram Parvin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000684.g006", "stats"=>{"downloads"=>2, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Treatment_of_a_MDA_MB_231_with_a_PPARG_inhibitor_indicates_reduction_in_the_proliferation_rate_/531080", "title"=>"Treatment of a MDA-MB-231 with a PPARG-inhibitor indicates reduction in the proliferation rate.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-02-26 00:18:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/860728"], "description"=>"<p>(A–B) Localization of PPAR in normal and triple negative of human mammary tissue sections indicates that (i) in normal tissue, localization is apical and unbound to the nuclear regions, and (ii) in triple negative tissue, localization is nuclear-bound and heterogeneous. (C–D) Quantitative analysis on a cell-by-cell basis indicates that PPAR (i) is upregulated in triple negative patients, and (ii) has a heterogeneous distribution.</p>", "links"=>[], "tags"=>["triple", "cancer"], "article_id"=>531179, "categories"=>["Information And Computing Sciences", "Molecular Biology", "Cell Biology", "Medicine"], "users"=>["Ju Han", "Hang Chang", "Orsi Giricz", "Genee Y. Lee", "Frederick L. Baehner", "Joe W. Gray", "Mina J. Bissell", "Paraic A. Kenny", "Bahram Parvin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000684.g007", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_PPARG_is_expressed_in_triple_negative_human_breast_cancer_tissue_/531179", "title"=>"PPARG is expressed in triple negative human breast cancer tissue.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-02-26 00:19:39"}
  • {"files"=>["https://ndownloader.figshare.com/files/860868"], "description"=>"<p>At each scale, mean filter response is invariant to rotation.</p>", "links"=>[], "tags"=>["elliptical", "contours", "half-peak", "iso-curves", "gabor", "orientations"], "article_id"=>531308, "categories"=>["Information And Computing Sciences", "Molecular Biology", "Cell Biology", "Medicine"], "users"=>["Ju Han", "Hang Chang", "Orsi Giricz", "Genee Y. Lee", "Frederick L. Baehner", "Joe W. Gray", "Mina J. Bissell", "Paraic A. Kenny", "Bahram Parvin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000684.g008", "stats"=>{"downloads"=>4, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_elliptical_contours_indicate_the_half_peak_magnitude_iso_curves_of_the_Gabor_filters_in_the_frequency_domain_at_6_orientations_and_4_scales_/531308", "title"=>"The elliptical contours indicate the half-peak magnitude iso-curves of the Gabor filters, in the frequency domain, at 6 orientations and 4 scales.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-02-26 00:21:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/860347"], "description"=>"<p>(A) CDF for each cluster, and (B) change in CDF as a function of cluster size, indicates that three is the optimum number of sub-populations.</p>", "links"=>[], "tags"=>["cdf", "computed"], "article_id"=>530802, "categories"=>["Information And Computing Sciences", "Molecular Biology", "Cell Biology", "Medicine"], "users"=>["Ju Han", "Hang Chang", "Orsi Giricz", "Genee Y. Lee", "Frederick L. Baehner", "Joe W. Gray", "Mina J. Bissell", "Paraic A. Kenny", "Bahram Parvin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000684.g003", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_CDF_and_its_derivative_computed_from_the_consensus_matrix_is_used_to_identify_the_number_of_clusters_/530802", "title"=>"The CDF and its derivative, computed from the consensus matrix, is used to identify the number of clusters.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-02-26 00:13:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/860414"], "description"=>"<p>All other cell lines are grouped in a different subpopulation.</p>", "links"=>[], "tags"=>["lines", "displaying", "phenotypes", "discovered"], "article_id"=>530866, "categories"=>["Information And Computing Sciences", "Molecular Biology", "Cell Biology", "Medicine"], "users"=>["Ju Han", "Hang Chang", "Orsi Giricz", "Genee Y. Lee", "Frederick L. Baehner", "Joe W. Gray", "Mina J. Bissell", "Paraic A. Kenny", "Bahram Parvin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000684.g004", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Three_cell_lines_displaying_aggressive_phenotypes_are_discovered_with_/530866", "title"=>"Three cell lines displaying aggressive phenotypes are discovered with .", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-02-26 00:14:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/860502"], "description"=>"<p>Three subpopulations of the 24 breast cancer cell lines grown in three-dimensional cell culture assay are revealed through consensus clustering.</p>", "links"=>[], "tags"=>["subpopulations", "24", "cancer", "lines", "grown", "three-dimensional", "assay", "revealed"], "article_id"=>530942, "categories"=>["Information And Computing Sciences", "Molecular Biology", "Cell Biology", "Medicine"], "users"=>["Ju Han", "Hang Chang", "Orsi Giricz", "Genee Y. Lee", "Frederick L. Baehner", "Joe W. Gray", "Mina J. Bissell", "Paraic A. Kenny", "Bahram Parvin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000684.g005", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Three_subpopulations_of_the_24_breast_cancer_cell_lines_grown_in_three_dimensional_cell_culture_assay_are_revealed_through_consensus_clustering_/530942", "title"=>"Three subpopulations of the 24 breast cancer cell lines grown in three-dimensional cell culture assay are revealed through consensus clustering.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-02-26 00:15:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/860173"], "description"=>"<p>Computational pipeline for differential and association studies between colony morphologies and gene profiles for the panel of breast cancer cell lines cultured in 3D.</p>", "links"=>[], "tags"=>["pipeline", "differential", "studies", "morphologies", "profiles", "cancer", "lines", "cultured"], "article_id"=>530616, "categories"=>["Information And Computing Sciences", "Molecular Biology", "Cell Biology", "Medicine"], "users"=>["Ju Han", "Hang Chang", "Orsi Giricz", "Genee Y. Lee", "Frederick L. Baehner", "Joe W. Gray", "Mina J. Bissell", "Paraic A. Kenny", "Bahram Parvin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000684.g001", "stats"=>{"downloads"=>2, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Computational_pipeline_for_differential_and_association_studies_between_colony_morphologies_and_gene_profiles_for_the_panel_of_breast_cancer_cell_lines_cultured_in_3D_/530616", "title"=>"Computational pipeline for differential and association studies between colony morphologies and gene profiles for the panel of breast cancer cell lines cultured in 3D.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-02-26 00:10:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/861039"], "description"=>"<p>Best genes for predicting the stellate cluster based on moderated t-statistic ().</p>", "links"=>[], "tags"=>["genes", "predicting", "stellate", "moderated", "t-statistic"], "article_id"=>531482, "categories"=>["Information And Computing Sciences", "Molecular Biology", "Cell Biology", "Medicine"], "users"=>["Ju Han", "Hang Chang", "Orsi Giricz", "Genee Y. Lee", "Frederick L. Baehner", "Joe W. Gray", "Mina J. Bissell", "Paraic A. Kenny", "Bahram Parvin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000684.t001", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Best_genes_for_predicting_the_stellate_cluster_based_on_moderated_t_statistic_/531482", "title"=>"Best genes for predicting the stellate cluster based on moderated t-statistic ().", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-02-26 00:24:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/860940"], "description"=>"<p>(a)(c) original images of two types of colonies with contrast reversal (e.g., dark regions in the bottom row versus bright regions in the top row), and (b)(d) the corresponding segmented results. Segmentation is feasible as a result of the Gabor filter bank that encodes oriented texture features.</p>", "links"=>[], "tags"=>["multicellular", "colonies", "differentiated", "computational"], "article_id"=>531390, "categories"=>["Information And Computing Sciences", "Molecular Biology", "Cell Biology", "Medicine"], "users"=>["Ju Han", "Hang Chang", "Orsi Giricz", "Genee Y. Lee", "Frederick L. Baehner", "Joe W. Gray", "Mina J. Bissell", "Paraic A. Kenny", "Bahram Parvin"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000684.g009", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Regions_associated_with_the_multicellular_colonies_are_differentiated_through_proposed_computational_method_/531390", "title"=>"Regions associated with the multicellular colonies are differentiated through proposed computational method.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-02-26 00:23:10"}

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  • {"unique-ip"=>"10", "full-text"=>"9", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"4", "year"=>"2020", "month"=>"2"}
  • {"unique-ip"=>"8", "full-text"=>"6", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"3"}
  • {"unique-ip"=>"16", "full-text"=>"19", "pdf"=>"12", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"4"}
  • {"unique-ip"=>"10", "full-text"=>"10", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"5"}
  • {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"6"}
  • {"unique-ip"=>"7", "full-text"=>"3", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2020", "month"=>"7"}
  • {"unique-ip"=>"6", "full-text"=>"4", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "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"=>"2020", "month"=>"9"}

Relative Metric

{"start_date"=>"2010-01-01T00:00:00Z", "end_date"=>"2010-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[288, 576, 733, 867, 984, 1087, 1182, 1267, 1346, 1424, 1501, 1577, 1646, 1711, 1778, 1841, 1908, 1970, 2034, 2102, 2162, 2227, 2296, 2359, 2422, 2482, 2550, 2610, 2679, 2747, 2820, 2887, 2955, 3009, 3067, 3130, 3200, 3257, 3322, 3379, 3443, 3507, 3571, 3632, 3683, 3753, 3822, 3877]}, {"subject_area"=>"/Biology and life sciences/Developmental biology", "average_usage"=>[265, 560, 722, 863, 978, 1083, 1172, 1261, 1345, 1428, 1488, 1559, 1630, 1701, 1764, 1840, 1899, 1965, 2028, 2088, 2150, 2211, 2270, 2348, 2410, 2461, 2531, 2598, 2645, 2719, 2793, 2870, 2923, 2974, 3020, 3080, 3142, 3198, 3259, 3351, 3418, 3471, 3527, 3581, 3637, 3706, 3761, 3817, 3872]}, {"subject_area"=>"/Medicine and health sciences/Oncology", "average_usage"=>[266, 580, 762, 935, 1085, 1218, 1336, 1459, 1581, 1680, 1759, 1835, 1914, 1994, 2067, 2144, 2213, 2278, 2341, 2423, 2496, 2581, 2672, 2768, 2836, 2898, 2978, 3068, 3137, 3218, 3284, 3351, 3420, 3465, 3549, 3629, 3696, 3756, 3819, 3875, 3938, 3985, 4038, 4103, 4177, 4246, 4321, 4382, 4449]}, {"subject_area"=>"/Physical sciences", "average_usage"=>[286, 543, 687, 806, 915, 1004, 1092, 1169, 1234, 1309, 1372, 1435, 1502, 1563, 1627, 1685, 1747, 1796, 1859, 1921, 1977, 2032, 2093, 2157, 2210, 2278, 2333, 2406, 2463, 2535, 2590, 2642, 2692, 2753, 2813, 2872, 2941, 2989, 3040, 3080, 3151, 3218, 3269, 3323, 3375, 3437, 3500, 3550, 3604]}, {"subject_area"=>"/Physical sciences/Mathematics", "average_usage"=>[314, 590, 728, 851, 953, 1050, 1127, 1206, 1276, 1336, 1390, 1451, 1504, 1569, 1619, 1674, 1732, 1792, 1851, 1900, 1959, 2004, 2076, 2126, 2182, 2239, 2292, 2353, 2427, 2522, 2595, 2676, 2735, 2785, 2836, 2893, 2943, 2993, 3041, 3097, 3160, 3214, 3251, 3299, 3357, 3428, 3482, 3515, 3555]}]}
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