Calculating Orthologs in Bacteria and Archaea: A Divide and Conquer Approach
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{"title"=>"Calculating orthologs in bacteria and archaea: A divide and conquer approach", "type"=>"journal", "authors"=>[{"first_name"=>"Mihail R.", "last_name"=>"Halachev", "scopus_author_id"=>"14034385100"}, {"first_name"=>"Nicholas J.", "last_name"=>"Loman", "scopus_author_id"=>"6701414703"}, {"first_name"=>"Mark J.", "last_name"=>"Pallen", "scopus_author_id"=>"7005883114"}], "year"=>2011, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"83155164533", "doi"=>"10.1371/journal.pone.0028388", "pui"=>"363066895", "pmid"=>"22174796", "scopus"=>"2-s2.0-83155164533", "issn"=>"19326203", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)"}, "id"=>"5fc1a7e9-8fba-38b5-955b-0504a53b1cf5", "abstract"=>"Among proteins, orthologs are defined as those that are derived by vertical descent from a single progenitor in the last common ancestor of their host organisms. Our goal is to compute a complete set of protein orthologs derived from all currently available complete bacterial and archaeal genomes. Traditional approaches typically rely on all-against-all BLAST searching which is prohibitively expensive in terms of hardware requirements or computational time (requiring an estimated 18 months or more on a typical server). Here, we present xBASE-Orth, a system for ongoing ortholog annotation, which applies a \"divide and conquer\" approach and adopts a pragmatic scheme that trades accuracy for speed. Starting at species level, xBASE-Orth carefully constructs and uses pan-genomes as proxies for the full collections of coding sequences at each level as it progressively climbs the taxonomic tree using the previously computed data. This leads to a significant decrease in the number of alignments that need to be performed, which translates into faster computation, making ortholog computation possible on a global scale. Using xBASE-Orth, we analyzed an NCBI collection of 1,288 bacterial and 94 archaeal complete genomes with more than 4 million coding sequences in 5 weeks and predicted more than 700 million ortholog pairs, clustered in 175,531 orthologous groups. We have also identified sets of highly conserved bacterial and archaeal orthologs and in so doing have highlighted anomalies in genome annotation and in the proposed composition of the minimal bacterial genome. In summary, our approach allows for scalable and efficient computation of the bacterial and archaeal ortholog annotations. In addition, due to its hierarchical nature, it is suitable for incorporating novel complete genomes and alternative genome annotations. The computed ortholog data and a continuously evolving set of applications based on it are integrated in the xBASE database, available at http://www.xbase.ac.uk/.", "link"=>"http://www.mendeley.com/research/calculating-orthologs-bacteria-archaea-divide-conquer-approach", "reader_count"=>77, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>3, "Researcher"=>25, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>20, "Student > Postgraduate"=>4, "Student > Master"=>10, "Student > Bachelor"=>2, "Lecturer"=>2, "Professor"=>7}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>3, "Researcher"=>25, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>20, "Student > Postgraduate"=>4, "Student > Master"=>10, "Student > Bachelor"=>2, "Lecturer"=>2, "Professor"=>7}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Unspecified"=>1, "Biochemistry, Genetics and Molecular Biology"=>4, "Agricultural and Biological Sciences"=>66, "Computer Science"=>3, "Immunology and Microbiology"=>1, "Earth and Planetary Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>66}, "Computer Science"=>{"Computer Science"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>4}, "Unspecified"=>{"Unspecified"=>1}}, "reader_count_by_country"=>{"Sweden"=>1, "United States"=>5, "Norway"=>1, "Denmark"=>1, "Brazil"=>2, "Poland"=>1, "United Kingdom"=>2, "Mexico"=>1, "France"=>2, "Chile"=>1, "Germany"=>2, "Spain"=>3}, "group_count"=>2}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/357368", "https://ndownloader.figshare.com/files/357386", "https://ndownloader.figshare.com/files/357431"], "description"=>"<div><p>Among proteins, orthologs are defined as those that are derived by vertical descent from a single progenitor in the last common ancestor of their host organisms. Our goal is to compute a complete set of protein orthologs derived from all currently available complete bacterial and archaeal genomes. Traditional approaches typically rely on all-against-all BLAST searching which is prohibitively expensive in terms of hardware requirements or computational time (requiring an estimated 18 months or more on a typical server). Here, we present xBASE-Orth, a system for ongoing ortholog annotation, which applies a “divide and conquer” approach and adopts a pragmatic scheme that trades accuracy for speed. Starting at species level, xBASE-Orth carefully constructs and uses pan-genomes as proxies for the full collections of coding sequences at each level as it progressively climbs the taxonomic tree using the previously computed data. This leads to a significant decrease in the number of alignments that need to be performed, which translates into faster computation, making ortholog computation possible on a global scale. Using xBASE-Orth, we analyzed an NCBI collection of 1,288 bacterial and 94 archaeal complete genomes with more than 4 million coding sequences in 5 weeks and predicted more than 700 million ortholog pairs, clustered in 175,531 orthologous groups. We have also identified sets of highly conserved bacterial and archaeal orthologs and in so doing have highlighted anomalies in genome annotation and in the proposed composition of the minimal bacterial genome. In summary, our approach allows for scalable and efficient computation of the bacterial and archaeal ortholog annotations. In addition, due to its hierarchical nature, it is suitable for incorporating novel complete genomes and alternative genome annotations. The computed ortholog data and a continuously evolving set of applications based on it are integrated in the xBASE database, available at <a href=\"http://www.xbase.ac.uk/\">http://www.xbase.ac.uk/</a>.</p> </div>", "links"=>[], "tags"=>["calculating", "orthologs", "conquer"], "article_id"=>130617, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Microbiology"], "users"=>["Mihail R. Halachev", "Nicholas J. Loman", "Mark J. Pallen"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0028388.s001", "https://dx.doi.org/10.1371/journal.pone.0028388.s002", "https://dx.doi.org/10.1371/journal.pone.0028388.s003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Calculating_Orthologs_in_Bacteria_and_Archaea_A_Divide_and_Conquer_Approach/130617", "title"=>"Calculating Orthologs in Bacteria and Archaea: A Divide and Conquer Approach", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2011-12-12 00:10:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/703430"], "description"=>"<p>xBASE-Orth computes the ortholog pairs by climbing up taxonomic levels and using the results at lower levels as part of the input for higher levels. At species level, for each species with two or more complete genomes, we compute the orthologs for each pair of genomes (see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0028388#s4\" target=\"_blank\">Methods</a>). At genus level, for each genus with two or more species with at least one complete genome, we compute the orthologs for each inter-species genome pair. For details on how the species ortholog data is used in ortholog computation at genus level, see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0028388#s4\" target=\"_blank\">Methods</a>. The orthologue computation at higher levels proceeds similarly.</p>", "links"=>[], "tags"=>["ortholog", "pairs", "analyzing", "prokaryotic"], "article_id"=>373800, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Microbiology"], "users"=>["Mihail R. Halachev", "Nicholas J. Loman", "Mark J. Pallen"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0028388.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Discovered_Ortholog_Pairs_OP_analyzing_1_382_complete_prokaryotic_genomes_/373800", "title"=>"Discovered Ortholog Pairs (OP) analyzing 1,382 complete prokaryotic genomes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-12 01:03:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/703503"], "description"=>"<p>Using single-linkage approach, the computed orthologs are organized in ortholog groups (OGs). Each CDS is clustered to an OG if it forms an ortholog pair with at least one CDS from the group and each CDS is included in one OG only. The x-axis lists 10 possible bins for the observed percentage of genomes in which CDSs from a particular OG are found. The y-axis denotes the fraction of all CDSs found for each bin. In agreement with previous reports, a significant fraction of CDSs are found only in a small percentage of genomes (less than in 10% of the considered archaeal or bacterial genomes, these also include singletons/orphans) forming the “accessory pool”; about 10% of the CDSs have orthologs in more than 90% of the genomes - the “extended core”.</p>", "links"=>[], "tags"=>["cdss", "occurrence", "94", "archaeal", "bacterial"], "article_id"=>373871, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Microbiology"], "users"=>["Mihail R. Halachev", "Nicholas J. Loman", "Mark J. Pallen"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0028388.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Frequency_of_CDSs_occurrence_in_the_94_archaeal_and_1_288_bacterial_genomes_/373871", "title"=>"Frequency of CDSs occurrence in the 94 archaeal and 1,288 bacterial genomes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-12 01:04:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/703563"], "description"=>"<p>By adopting practical accuracy/speed trade-off xBASE-Orth allows for acceptable computational time using reasonable hardware resources and is predicted to be about 15 times faster compared to direct application of OrthoMCL. The vast majority of the computation time is spent performing CDS alignments and operating on the smaller pan-genomes (xBASE-Orth) rather than on the full CDS collection (OrthoMCL) results in significant time advantage. It is more prominent at higher taxonomic levels, where the difference between pan-genome and full CDS collection sizes increases.</p>", "links"=>[], "tags"=>["times", "speedup", "compared"], "article_id"=>373931, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Microbiology"], "users"=>["Mihail R. Halachev", "Nicholas J. Loman", "Mark J. Pallen"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0028388.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Computation_times_and_estimated_speedup_compared_to_OrthoMCL_/373931", "title"=>"Computation times and estimated speedup compared to OrthoMCL.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-12 01:05:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/703623"], "description"=>"<p>xBASE-Orth has a significant speed advantage over direct application of OrthoMCL which comes at the possible cost of decreased accuracy. We compared the performance of the two approaches over three distinct phyla – Bacteroidetes (40 complete genomes), Cyanobacteria (41 genomes) and Euryarchaeota (62 genomes), computing orthologs at genus, family, order and phylum level. At higher taxonomic levels the pan-genome sizes are significantly smaller compared to the full CDS collections - about half at order level and only about one third at phylum level for the datasets analyzed here (CR stands for Compression Ratio = [Number of CDSs in pan-genomes used by xBASE-Orth/Number of CDSs used by OrthoMCL] * 100%). Hence, at higher levels each CDS in a pan-genome is a representative of a larger set of orthologous/paralogous CDSs, plausibly becoming less sensitive and specific. Compared to the OrthoMCL results, it appears that on average the xBASE-Orth results contain from 1% (at genus level) to 9.7% (phylum) additional ortholog pairs, while failing to detect from 0.5% (genus) to 14% (phylum) OrthoMCL pairs.</p>", "links"=>[], "tags"=>["orthomcl"], "article_id"=>373996, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Microbiology"], "users"=>["Mihail R. Halachev", "Nicholas J. Loman", "Mark J. Pallen"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0028388.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_xBASE_Orth_vs_OrthoMCL_comparison_/373996", "title"=>"xBASE-Orth vs. OrthoMCL comparison.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-12 01:06:36"}
  • {"files"=>["https://ndownloader.figshare.com/files/703696"], "description"=>"<p>To investigate the specificity of xBASE-Orth we selected 2,384 CDSs such that: <i>i</i>) each CDS has at least one ortholog at each taxonomic level; <i>ii</i>) it has no more than 150 orthologs in total; and <i>iii</i>) the ortholog groups (OGs) for each of the 2,384 CDSs are disjoint. For each of the CDSs, we fetched the orthologs predicted by xBASE-Orth, performed multiple alignment of the sequences with ClustalW2, and scored the alignment with the norMD tool. The x-axis lists the chosen bin ranges for the norMD value. The y-axis depicts the distribution of the observed norMD values across the bins. A value of 0.5 or greater is considered to be the cut-off value for a good multiple alignment, indicating high level of sequence similarity. A vast majority (84%) of the chosen 2,384 OGs exhibit suitable sequence similarity and align well, producing norMD values ≥0.5. It is worth noting that on average about 60% of the orthologs fetched for each of the 2,384 CDSs are at phylum and domain level – i.e. xBASE-Orth exhibits good specificity even at large evolutionary distances.</p>", "links"=>[], "tags"=>["normd", "scores"], "article_id"=>374063, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Microbiology"], "users"=>["Mihail R. Halachev", "Nicholas J. Loman", "Mark J. Pallen"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0028388.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_norMD_scores_for_the_2_384_multiple_alignments_/374063", "title"=>"Distribution of norMD scores for the 2,384 multiple alignments.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-12 01:07:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/703765"], "description"=>"<p>For details on potential bacterial core CDSs, see Dataset S2; for details on potential archaeal core CDSs, see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0028388#pone.0028388.s003\" target=\"_blank\">Dataset S3</a>.</p>", "links"=>[], "tags"=>["bacterial"], "article_id"=>374134, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Microbiology"], "users"=>["Mihail R. Halachev", "Nicholas J. Loman", "Mark J. Pallen"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0028388.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_List_of_potential_bacterial_core_CDSs_/374134", "title"=>"List of potential bacterial core CDSs.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-12 01:08:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/703913"], "description"=>"<p>We define HCBOs (Highly Conserved Bacterial Orthologs) as CDSs that is present in at least 90% of the considered bacterial genomes. The COG functional assignment was performed using COGnitor.</p>", "links"=>[], "tags"=>["microbiology", "Computational biology", "computer science"], "article_id"=>374277, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Microbiology"], "users"=>["Mihail R. Halachev", "Nicholas J. Loman", "Mark J. Pallen"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0028388.g007"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Functional_category_distribution_of_HCBOs_/374277", "title"=>"Functional category distribution of HCBOs.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-12 01:11:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/704025"], "description"=>"<p>We evaluated the genome plasticity by two alternative methods: evaluation of the pan-genome as proposed by Tettelin <i>et al.. </i><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0028388#pone.0028388-Tettelin2\" target=\"_blank\">[42]</a> and computation of the genomic fluidity as proposed by Kislyuk <i>et al.. </i><a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0028388#pone.0028388-Kislyuk1\" target=\"_blank\">[52]</a>. The former approach is based on the assumption that in processing newly sequenced genomes from given species it will become increasingly harder to find novel CDSs and their number <i>n</i> grows according to a sub-linear power law <i>n</i> = <i>κ N</i><sup>−<i>α</i></sup> , where <i>N</i> is the number of genomes considered. Species with <i>α</i>>1 are said to have “closed” pan-genome, while species with <i>α</i>≤1 are said to have “open” pan-genomes. Since the results depend on the order in which genomes are considered, for the <i>n</i> values we used medians over 100 random genome order permutations for each species. In most cases the data fitted the model well, with R-squared (goodness-of-fit) values close to 1.0. The latter approach compares each pair of genomes within species to find the proportion of unique/shared CDSs and computes the median species genomic fluidity, where fluidity value of 0.2 implies that 20% of CDSs are unique to their host genomes, while 80% are shared.</p>", "links"=>[], "tags"=>["plasticity", "34"], "article_id"=>374391, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Microbiology"], "users"=>["Mihail R. Halachev", "Nicholas J. Loman", "Mark J. Pallen"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0028388.g008"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Genome_plasticity_for_34_species_with_at_least_5_complete_genomes_/374391", "title"=>"Genome plasticity for 34 species with at least 5 complete genomes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-12 01:13:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/704158"], "description"=>"<p>x-axis: number of genomes considered (<i>N</i> in the power law model), y-axis: number of new CDSs discovered at each iteration (<i>n</i> in the power law model), the curve fitted as power trendline (Excel 2007).</p>", "links"=>[], "tags"=>["microbiology", "Computational biology", "computer science"], "article_id"=>374519, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Microbiology"], "users"=>["Mihail R. Halachev", "Nicholas J. Loman", "Mark J. Pallen"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0028388.g009"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Species_with_closed_pan_genomes_/374519", "title"=>"Species with closed pan-genomes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-12 01:15:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/704294"], "description"=>"<p>x-axis: number of genomes considered (<i>N</i> in the power law model), y-axis: number of new CDSs discovered at each iteration (<i>n</i> in the power law model), the curve fitted as power trendline (Excel 2007).</p>", "links"=>[], "tags"=>["microbiology", "Computational biology", "computer science"], "article_id"=>374658, "categories"=>["Information And Computing Sciences", "Biological Sciences", "Microbiology"], "users"=>["Mihail R. Halachev", "Nicholas J. Loman", "Mark J. Pallen"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0028388.g010"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Species_with_open_pan_genomes_/374658", "title"=>"Species with open pan-genomes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-12-12 01:17:38"}

PMC Usage Stats | Further Information

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  • {"month"=>"4", "scanned-page-browse"=>"0", "cited-by"=>"0", "abstract"=>"2", "full-text"=>"12", "year"=>"2012", "pdf"=>"6", "unique-ip"=>"15", "figure"=>"9", "scanned-summary"=>"0", "supp-data"=>"2"}
  • {"scanned-page-browse"=>"0", "month"=>"5", "cited-by"=>"0", "abstract"=>"2", "full-text"=>"9", "unique-ip"=>"12", "pdf"=>"9", "year"=>"2012", "figure"=>"5", "scanned-summary"=>"0", "supp-data"=>"0"}
  • {"month"=>"6", "scanned-page-browse"=>"0", "cited-by"=>"0", "abstract"=>"0", "full-text"=>"19", "year"=>"2012", "pdf"=>"3", "unique-ip"=>"14", "figure"=>"5", "scanned-summary"=>"0", "supp-data"=>"0"}
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  • {"unique-ip"=>"8", "full-text"=>"9", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2012", "month"=>"8"}
  • {"unique-ip"=>"8", "full-text"=>"15", "pdf"=>"4", "abstract"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2012", "month"=>"9"}
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  • {"unique-ip"=>"8", "full-text"=>"9", "pdf"=>"4", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2012", "month"=>"12"}
  • {"unique-ip"=>"6", "full-text"=>"9", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"1"}
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  • {"unique-ip"=>"5", "full-text"=>"3", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2013", "month"=>"6"}
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  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"8"}
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  • {"unique-ip"=>"3", "full-text"=>"5", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"5"}
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  • {"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"=>"2015", "month"=>"3"}
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  • {"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"=>"2015", "month"=>"8"}
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Relative Metric

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