MIDER: Network Inference with Mutual Information Distance and Entropy Reduction
Events
Loading … Spinner

Mendeley | Further Information

{"title"=>"MIDER: Network inference with mutual information distance and entropy reduction", "type"=>"journal", "authors"=>[{"first_name"=>"Alejandro F.", "last_name"=>"Villaverde", "scopus_author_id"=>"36344301700"}, {"first_name"=>"John", "last_name"=>"Ross", "scopus_author_id"=>"7404966799"}, {"first_name"=>"Federico", "last_name"=>"Morán", "scopus_author_id"=>"7006435621"}, {"first_name"=>"Julio R.", "last_name"=>"Banga", "scopus_author_id"=>"7102475138"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84900566215", "sgr"=>"84900566215", "issn"=>"19326203", "doi"=>"10.1371/journal.pone.0096732", "pmid"=>"24806471", "isbn"=>"19326203 (Electronic)", "pui"=>"373094188"}, "id"=>"f23879e0-f219-338e-b49f-bdbfe2c9dce8", "abstract"=>"The prediction of links among variables from a given dataset is a task referred to as network inference or reverse engineering. It is an open problem in bioinformatics and systems biology, as well as in other areas of science. Information theory, which uses concepts such as mutual information, provides a rigorous framework for addressing it. While a number of information-theoretic methods are already available, most of them focus on a particular type of problem, introducing assumptions that limit their generality. Furthermore, many of these methods lack a publicly available implementation. Here we present MIDER, a method for inferring network structures with information theoretic concepts. It consists of two steps: first, it provides a representation of the network in which the distance among nodes indicates their statistical closeness. Second, it refines the prediction of the existing links to distinguish between direct and indirect interactions and to assign directionality. The method accepts as input time-series data related to some quantitative features of the network nodes (such as e.g. concentrations, if the nodes are chemical species). It takes into account time delays between variables, and allows choosing among several definitions and normalizations of mutual information. It is general purpose: it may be applied to any type of network, cellular or otherwise. A Matlab implementation including source code and data is freely available (http://www.iim.csic.es/~gingproc/mider.html). The performance of MIDER has been evaluated on seven different benchmark problems that cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. Comparisons with state of the art information-theoretic methods have demonstrated the competitive performance of MIDER, as well as its versatility. Its use does not demand any a priori knowledge from the user; the default settings and the adaptive nature of the method provide good results for a wide range of problems without requiring tuning.", "link"=>"http://www.mendeley.com/research/mider-network-inference-mutual-information-distance-entropy-reduction", "reader_count"=>86, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>5, "Librarian"=>2, "Researcher"=>23, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>22, "Student > Postgraduate"=>1, "Other"=>5, "Student > Master"=>6, "Student > Bachelor"=>11, "Professor"=>4}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>5, "Librarian"=>2, "Researcher"=>23, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>22, "Student > Postgraduate"=>1, "Other"=>5, "Student > Master"=>6, "Student > Bachelor"=>11, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Agricultural and Biological Sciences"=>22, "Arts and Humanities"=>1, "Chemistry"=>1, "Computer Science"=>18, "Engineering"=>14, "Environmental Science"=>3, "Biochemistry, Genetics and Molecular Biology"=>12, "Mathematics"=>4, "Medicine and Dentistry"=>1, "Sports and Recreations"=>1, "Physics and Astronomy"=>5, "Social Sciences"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Social Sciences"=>{"Social Sciences"=>2}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>5}, "Mathematics"=>{"Mathematics"=>4}, "Unspecified"=>{"Unspecified"=>2}, "Environmental Science"=>{"Environmental Science"=>3}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Engineering"=>{"Engineering"=>14}, "Chemistry"=>{"Chemistry"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>22}, "Computer Science"=>{"Computer Science"=>18}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>12}}, "reader_count_by_country"=>{"Canada"=>1, "United States"=>1, "Denmark"=>1, "Mexico"=>1, "France"=>1, "Chile"=>1, "Switzerland"=>1, "India"=>1, "Spain"=>1}, "group_count"=>3}

CrossRef

Scopus | Further Information

{"@_fa"=>"true", "link"=>[{"@_fa"=>"true", "@ref"=>"self", "@href"=>"https://api.elsevier.com/content/abstract/scopus_id/84900566215"}, {"@_fa"=>"true", "@ref"=>"author-affiliation", "@href"=>"https://api.elsevier.com/content/abstract/scopus_id/84900566215?field=author,affiliation"}, {"@_fa"=>"true", "@ref"=>"scopus", "@href"=>"https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84900566215&origin=inward"}, {"@_fa"=>"true", "@ref"=>"scopus-citedby", "@href"=>"https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=84900566215&origin=inward"}], "prism:url"=>"https://api.elsevier.com/content/abstract/scopus_id/84900566215", "dc:identifier"=>"SCOPUS_ID:84900566215", "eid"=>"2-s2.0-84900566215", "dc:title"=>"MIDER: Network inference with mutual information distance and entropy reduction", "dc:creator"=>"Villaverde A.", "prism:publicationName"=>"PLoS ONE", "prism:eIssn"=>"19326203", "prism:volume"=>"9", "prism:issueIdentifier"=>"5", "prism:pageRange"=>nil, "prism:coverDate"=>"2014-05-07", "prism:coverDisplayDate"=>"7 May 2014", "prism:doi"=>"10.1371/journal.pone.0096732", "citedby-count"=>"54", "affiliation"=>[{"@_fa"=>"true", "affilname"=>"CSIC - Instituto de Investigaciones Marinas (IIM)", "affiliation-city"=>"Vigo", "affiliation-country"=>"Spain"}], "pubmed-id"=>"24806471", "prism:aggregationType"=>"Journal", "subtype"=>"ar", "subtypeDescription"=>"Article", "article-number"=>"e96732", "source-id"=>"10600153309", "openaccess"=>"1", "openaccessFlag"=>true}

Facebook

  • {"url"=>"http%3A%2F%2Fjournals.plos.org%2Fplosone%2Farticle%3Fid%3D10.1371%252Fjournal.pone.0096732", "share_count"=>0, "like_count"=>0, "comment_count"=>0, "click_count"=>0, "total_count"=>0}

Twitter

Counter

  • {"month"=>"5", "year"=>"2014", "pdf_views"=>"58", "xml_views"=>"6", "html_views"=>"395"}
  • {"month"=>"6", "year"=>"2014", "pdf_views"=>"47", "xml_views"=>"1", "html_views"=>"159"}
  • {"month"=>"7", "year"=>"2014", "pdf_views"=>"21", "xml_views"=>"0", "html_views"=>"135"}
  • {"month"=>"8", "year"=>"2014", "pdf_views"=>"30", "xml_views"=>"2", "html_views"=>"104"}
  • {"month"=>"9", "year"=>"2014", "pdf_views"=>"34", "xml_views"=>"1", "html_views"=>"114"}
  • {"month"=>"10", "year"=>"2014", "pdf_views"=>"29", "xml_views"=>"1", "html_views"=>"133"}
  • {"month"=>"11", "year"=>"2014", "pdf_views"=>"39", "xml_views"=>"2", "html_views"=>"187"}
  • {"month"=>"12", "year"=>"2014", "pdf_views"=>"20", "xml_views"=>"1", "html_views"=>"88"}
  • {"month"=>"1", "year"=>"2015", "pdf_views"=>"19", "xml_views"=>"0", "html_views"=>"117"}
  • {"month"=>"2", "year"=>"2015", "pdf_views"=>"18", "xml_views"=>"0", "html_views"=>"122"}
  • {"month"=>"3", "year"=>"2015", "pdf_views"=>"14", "xml_views"=>"0", "html_views"=>"117"}
  • {"month"=>"4", "year"=>"2015", "pdf_views"=>"22", "xml_views"=>"0", "html_views"=>"151"}
  • {"month"=>"5", "year"=>"2015", "pdf_views"=>"32", "xml_views"=>"1", "html_views"=>"109"}
  • {"month"=>"6", "year"=>"2015", "pdf_views"=>"12", "xml_views"=>"1", "html_views"=>"95"}
  • {"month"=>"7", "year"=>"2015", "pdf_views"=>"24", "xml_views"=>"0", "html_views"=>"124"}
  • {"month"=>"8", "year"=>"2015", "pdf_views"=>"18", "xml_views"=>"1", "html_views"=>"69"}
  • {"month"=>"9", "year"=>"2015", "pdf_views"=>"24", "xml_views"=>"2", "html_views"=>"138"}
  • {"month"=>"10", "year"=>"2015", "pdf_views"=>"13", "xml_views"=>"1", "html_views"=>"142"}
  • {"month"=>"11", "year"=>"2015", "pdf_views"=>"19", "xml_views"=>"0", "html_views"=>"185"}
  • {"month"=>"12", "year"=>"2015", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"139"}
  • {"month"=>"1", "year"=>"2016", "pdf_views"=>"18", "xml_views"=>"0", "html_views"=>"168"}
  • {"month"=>"2", "year"=>"2016", "pdf_views"=>"10", "xml_views"=>"0", "html_views"=>"142"}
  • {"month"=>"3", "year"=>"2016", "pdf_views"=>"12", "xml_views"=>"1", "html_views"=>"157"}
  • {"month"=>"4", "year"=>"2016", "pdf_views"=>"23", "xml_views"=>"0", "html_views"=>"95"}
  • {"month"=>"5", "year"=>"2016", "pdf_views"=>"28", "xml_views"=>"0", "html_views"=>"93"}
  • {"month"=>"6", "year"=>"2016", "pdf_views"=>"31", "xml_views"=>"0", "html_views"=>"147"}
  • {"month"=>"7", "year"=>"2016", "pdf_views"=>"15", "xml_views"=>"0", "html_views"=>"73"}
  • {"month"=>"8", "year"=>"2016", "pdf_views"=>"32", "xml_views"=>"0", "html_views"=>"91"}
  • {"month"=>"9", "year"=>"2016", "pdf_views"=>"19", "xml_views"=>"0", "html_views"=>"114"}
  • {"month"=>"10", "year"=>"2016", "pdf_views"=>"33", "xml_views"=>"0", "html_views"=>"133"}
  • {"month"=>"11", "year"=>"2016", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"121"}
  • {"month"=>"12", "year"=>"2016", "pdf_views"=>"36", "xml_views"=>"0", "html_views"=>"129"}
  • {"month"=>"1", "year"=>"2017", "pdf_views"=>"27", "xml_views"=>"2", "html_views"=>"139"}
  • {"month"=>"2", "year"=>"2017", "pdf_views"=>"39", "xml_views"=>"0", "html_views"=>"251"}
  • {"month"=>"3", "year"=>"2017", "pdf_views"=>"26", "xml_views"=>"0", "html_views"=>"268"}
  • {"month"=>"4", "year"=>"2017", "pdf_views"=>"24", "xml_views"=>"0", "html_views"=>"184"}
  • {"month"=>"5", "year"=>"2017", "pdf_views"=>"26", "xml_views"=>"3", "html_views"=>"136"}
  • {"month"=>"6", "year"=>"2017", "pdf_views"=>"21", "xml_views"=>"0", "html_views"=>"107"}
  • {"month"=>"7", "year"=>"2017", "pdf_views"=>"19", "xml_views"=>"1", "html_views"=>"94"}
  • {"month"=>"8", "year"=>"2017", "pdf_views"=>"23", "xml_views"=>"1", "html_views"=>"113"}
  • {"month"=>"9", "year"=>"2017", "pdf_views"=>"23", "xml_views"=>"1", "html_views"=>"109"}
  • {"month"=>"10", "year"=>"2017", "pdf_views"=>"29", "xml_views"=>"2", "html_views"=>"145"}
  • {"month"=>"11", "year"=>"2017", "pdf_views"=>"16", "xml_views"=>"1", "html_views"=>"170"}
  • {"month"=>"12", "year"=>"2017", "pdf_views"=>"29", "xml_views"=>"3", "html_views"=>"134"}
  • {"month"=>"1", "year"=>"2018", "pdf_views"=>"18", "xml_views"=>"0", "html_views"=>"120"}
  • {"month"=>"2", "year"=>"2018", "pdf_views"=>"36", "xml_views"=>"0", "html_views"=>"73"}
  • {"month"=>"3", "year"=>"2018", "pdf_views"=>"30", "xml_views"=>"2", "html_views"=>"76"}
  • {"month"=>"4", "year"=>"2018", "pdf_views"=>"40", "xml_views"=>"0", "html_views"=>"44"}
  • {"month"=>"5", "year"=>"2018", "pdf_views"=>"42", "xml_views"=>"2", "html_views"=>"52"}
  • {"month"=>"6", "year"=>"2018", "pdf_views"=>"26", "xml_views"=>"1", "html_views"=>"41"}
  • {"month"=>"7", "year"=>"2018", "pdf_views"=>"22", "xml_views"=>"3", "html_views"=>"58"}
  • {"month"=>"8", "year"=>"2018", "pdf_views"=>"33", "xml_views"=>"1", "html_views"=>"45"}
  • {"month"=>"9", "year"=>"2018", "pdf_views"=>"24", "xml_views"=>"0", "html_views"=>"27"}
  • {"month"=>"10", "year"=>"2018", "pdf_views"=>"27", "xml_views"=>"2", "html_views"=>"59"}
  • {"month"=>"11", "year"=>"2018", "pdf_views"=>"34", "xml_views"=>"0", "html_views"=>"74"}
  • {"month"=>"12", "year"=>"2018", "pdf_views"=>"30", "xml_views"=>"0", "html_views"=>"53"}
  • {"month"=>"1", "year"=>"2019", "pdf_views"=>"13", "xml_views"=>"1", "html_views"=>"36"}
  • {"month"=>"2", "year"=>"2019", "pdf_views"=>"16", "xml_views"=>"0", "html_views"=>"42"}
  • {"month"=>"3", "year"=>"2019", "pdf_views"=>"21", "xml_views"=>"0", "html_views"=>"51"}
  • {"month"=>"4", "year"=>"2019", "pdf_views"=>"23", "xml_views"=>"0", "html_views"=>"54"}
  • {"month"=>"5", "year"=>"2019", "pdf_views"=>"46", "xml_views"=>"0", "html_views"=>"60"}
  • {"month"=>"6", "year"=>"2019", "pdf_views"=>"20", "xml_views"=>"0", "html_views"=>"67"}
  • {"month"=>"7", "year"=>"2019", "pdf_views"=>"22", "xml_views"=>"6", "html_views"=>"51"}
  • {"month"=>"8", "year"=>"2019", "pdf_views"=>"9", "xml_views"=>"0", "html_views"=>"25"}
  • {"month"=>"9", "year"=>"2019", "pdf_views"=>"13", "xml_views"=>"0", "html_views"=>"29"}

Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1488995"], "description"=>"<p>One of the MIDER outputs, shown for Benchmark B2: a 3D plot of the mutual information between a variable (X3) and the rest, for different time lags between variables.</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "biotechnology", "Bioengineering", "Biological systems engineering", "Biomedical Engineering", "Computational biology", "genome analysis", "Genetic networks", "genetics", "genomics", "systems biology", "Information technology", "databases", "information theory", "Network Analysis", "Metabolic networks", "Regulatory networks", "Signaling networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms"], "article_id"=>1019712, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Alejandro F. Villaverde", "John Ross", "Federico Morán", "Julio R. Banga"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096732.g002", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MI_plot_/1019712", "title"=>"MI plot.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-07 03:50:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/1488997"], "description"=>"<p>PR curves (recall in horizontal axis, precision in vertical axis) of all the benchmarks (B1–B7) for five network inference methods (ARACNE, CLR, MRNET, TDARACNE, and MIDER) and for the community prediction. Solid lines and small dots correspond to the (P,R) values obtained by changing the threshold for detecting interactions. Large square points correspond to the (P,R) values obtained with the default (out of the box) settings of each method.</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "biotechnology", "Bioengineering", "Biological systems engineering", "Biomedical Engineering", "Computational biology", "genome analysis", "Genetic networks", "genetics", "genomics", "systems biology", "Information technology", "databases", "information theory", "Network Analysis", "Metabolic networks", "Regulatory networks", "Signaling networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms"], "article_id"=>1019714, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Alejandro F. Villaverde", "John Ross", "Federico Morán", "Julio R. Banga"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096732.g003", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Precision_Recall_curves_/1019714", "title"=>"Precision-Recall curves.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-07 03:50:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/1488998"], "description"=>"<p>The color maps show precision (left panel) and recall (central panel) achieved by each method and for each benchmark with its default settings, as well as the area under precision-recall curve (AUPR, right panel). Numerical values are in the range [0–1], and are represented in colors according to the scale in the right (green  =  good, blue  =  bad).</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "biotechnology", "Bioengineering", "Biological systems engineering", "Biomedical Engineering", "Computational biology", "genome analysis", "Genetic networks", "genetics", "genomics", "systems biology", "Information technology", "databases", "information theory", "Network Analysis", "Metabolic networks", "Regulatory networks", "Signaling networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms"], "article_id"=>1019715, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Alejandro F. Villaverde", "John Ross", "Federico Morán", "Julio R. Banga"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096732.g004", "stats"=>{"downloads"=>0, "page_views"=>35, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_P_R_and_AUPR_/1019715", "title"=>"P, R, and AUPR.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-07 03:50:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/1489000"], "description"=>"<p>First reaction steps of glycolysis.</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "biotechnology", "Bioengineering", "Biological systems engineering", "Biomedical Engineering", "Computational biology", "genome analysis", "Genetic networks", "genetics", "genomics", "systems biology", "Information technology", "databases", "information theory", "Network Analysis", "Metabolic networks", "Regulatory networks", "Signaling networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms"], "article_id"=>1019717, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Alejandro F. Villaverde", "John Ross", "Federico Morán", "Julio R. Banga"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096732.g005", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Benchmark_B1_/1019717", "title"=>"Benchmark B1.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-07 03:50:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/1489001"], "description"=>"<p>Reaction chain with 8 species.</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "biotechnology", "Bioengineering", "Biological systems engineering", "Biomedical Engineering", "Computational biology", "genome analysis", "Genetic networks", "genetics", "genomics", "systems biology", "Information technology", "databases", "information theory", "Network Analysis", "Metabolic networks", "Regulatory networks", "Signaling networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms"], "article_id"=>1019718, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Alejandro F. Villaverde", "John Ross", "Federico Morán", "Julio R. Banga"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096732.g006", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Benchmark_B2_/1019718", "title"=>"Benchmark B2.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-07 03:50:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/1489003"], "description"=>"<p>Reaction chain with 4 species.</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "biotechnology", "Bioengineering", "Biological systems engineering", "Biomedical Engineering", "Computational biology", "genome analysis", "Genetic networks", "genetics", "genomics", "systems biology", "Information technology", "databases", "information theory", "Network Analysis", "Metabolic networks", "Regulatory networks", "Signaling networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms"], "article_id"=>1019720, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Alejandro F. Villaverde", "John Ross", "Federico Morán", "Julio R. Banga"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096732.g007", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Benchmark_B3_/1019720", "title"=>"Benchmark B3.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-07 03:50:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/1489004"], "description"=>"<p>IRMA.</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "biotechnology", "Bioengineering", "Biological systems engineering", "Biomedical Engineering", "Computational biology", "genome analysis", "Genetic networks", "genetics", "genomics", "systems biology", "Information technology", "databases", "information theory", "Network Analysis", "Metabolic networks", "Regulatory networks", "Signaling networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms"], "article_id"=>1019721, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Alejandro F. Villaverde", "John Ross", "Federico Morán", "Julio R. Banga"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096732.g008", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Benchmark_B4_/1019721", "title"=>"Benchmark B4.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-07 03:50:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/1489005"], "description"=>"<p>MAPK cascade.</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "biotechnology", "Bioengineering", "Biological systems engineering", "Biomedical Engineering", "Computational biology", "genome analysis", "Genetic networks", "genetics", "genomics", "systems biology", "Information technology", "databases", "information theory", "Network Analysis", "Metabolic networks", "Regulatory networks", "Signaling networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms"], "article_id"=>1019722, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Alejandro F. Villaverde", "John Ross", "Federico Morán", "Julio R. Banga"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096732.g009", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Benchmark_B5_/1019722", "title"=>"Benchmark B5.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-07 03:50:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/1489006"], "description"=>"<p>List of the benchmark problems used in the comparisons.</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "biotechnology", "Bioengineering", "Biological systems engineering", "Biomedical Engineering", "Computational biology", "genome analysis", "Genetic networks", "genetics", "genomics", "systems biology", "Information technology", "databases", "information theory", "Network Analysis", "Metabolic networks", "Regulatory networks", "Signaling networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms"], "article_id"=>1019723, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Alejandro F. Villaverde", "John Ross", "Federico Morán", "Julio R. Banga"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096732.t001", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Benchmarks_/1019723", "title"=>"Benchmarks.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-05-07 03:50:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/1489007"], "description"=>"<div><p>The prediction of links among variables from a given dataset is a task referred to as network inference or reverse engineering. It is an open problem in bioinformatics and systems biology, as well as in other areas of science. Information theory, which uses concepts such as mutual information, provides a rigorous framework for addressing it. While a number of information-theoretic methods are already available, most of them focus on a particular type of problem, introducing assumptions that limit their generality. Furthermore, many of these methods lack a publicly available implementation. Here we present MIDER, a method for inferring network structures with information theoretic concepts. It consists of two steps: first, it provides a representation of the network in which the distance among nodes indicates their statistical closeness. Second, it refines the prediction of the existing links to distinguish between direct and indirect interactions and to assign directionality. The method accepts as input time-series data related to some quantitative features of the network nodes (such as e.g. concentrations, if the nodes are chemical species). It takes into account time delays between variables, and allows choosing among several definitions and normalizations of mutual information. It is general purpose: it may be applied to any type of network, cellular or otherwise. A Matlab implementation including source code and data is freely available (<a href=\"http://www.iim.csic.es/~gingproc/mider.html\" target=\"_blank\">http://www.iim.csic.es/~gingproc/mider.html</a>). The performance of MIDER has been evaluated on seven different benchmark problems that cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. Comparisons with state of the art information–theoretic methods have demonstrated the competitive performance of MIDER, as well as its versatility. Its use does not demand any a priori knowledge from the user; the default settings and the adaptive nature of the method provide good results for a wide range of problems without requiring tuning.</p></div>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "biotechnology", "Bioengineering", "Biological systems engineering", "Biomedical Engineering", "Computational biology", "genome analysis", "Genetic networks", "genetics", "genomics", "systems biology", "Information technology", "databases", "information theory", "Network Analysis", "Metabolic networks", "Regulatory networks", "Signaling networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms", "inference", "entropy"], "article_id"=>1019724, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Alejandro F. Villaverde", "John Ross", "Federico Morán", "Julio R. Banga"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096732", "stats"=>{"downloads"=>2, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MIDER_Network_Inference_with_Mutual_Information_Distance_and_Entropy_Reduction_/1019724", "title"=>"MIDER: Network Inference with Mutual Information Distance and Entropy Reduction", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-05-07 03:50:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/1488994"], "description"=>"<p>MIDER workflow.</p>", "links"=>[], "tags"=>["Biochemistry", "Biochemical simulations", "biotechnology", "Bioengineering", "Biological systems engineering", "Biomedical Engineering", "Computational biology", "genome analysis", "Genetic networks", "genetics", "genomics", "systems biology", "Information technology", "databases", "information theory", "Network Analysis", "Metabolic networks", "Regulatory networks", "Signaling networks", "software engineering", "Software tools", "mathematics", "Applied mathematics", "algorithms"], "article_id"=>1019711, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Alejandro F. Villaverde", "John Ross", "Federico Morán", "Julio R. Banga"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096732.g001", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MIDER_workflow_/1019711", "title"=>"MIDER workflow.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-07 03:50:04"}

PMC Usage Stats | Further Information

  • {"unique-ip"=>"16", "full-text"=>"11", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"6", "cited-by"=>"0", "year"=>"2014", "month"=>"5"}
  • {"unique-ip"=>"13", "full-text"=>"14", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"6"}
  • {"unique-ip"=>"16", "full-text"=>"19", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"4"}
  • {"unique-ip"=>"10", "full-text"=>"15", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"5"}
  • {"unique-ip"=>"12", "full-text"=>"15", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"8", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2015", "month"=>"6"}
  • {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"7"}
  • {"unique-ip"=>"13", "full-text"=>"15", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"3"}
  • {"unique-ip"=>"19", "full-text"=>"18", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"2"}
  • {"unique-ip"=>"13", "full-text"=>"11", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"8"}
  • {"unique-ip"=>"12", "full-text"=>"9", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"6", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"9"}
  • {"unique-ip"=>"10", "full-text"=>"11", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"10"}
  • {"unique-ip"=>"9", "full-text"=>"4", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"7"}
  • {"unique-ip"=>"6", "full-text"=>"4", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"8"}
  • {"unique-ip"=>"11", "full-text"=>"9", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"9"}
  • {"unique-ip"=>"12", "full-text"=>"6", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2014", "month"=>"10"}
  • {"unique-ip"=>"5", "full-text"=>"4", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"2"}
  • {"unique-ip"=>"9", "full-text"=>"6", "pdf"=>"0", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"9", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"11"}
  • {"unique-ip"=>"9", "full-text"=>"8", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"12"}
  • {"unique-ip"=>"8", "full-text"=>"7", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"1"}
  • {"unique-ip"=>"18", "full-text"=>"13", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2015", "month"=>"11"}
  • {"unique-ip"=>"14", "full-text"=>"9", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"12"}
  • {"unique-ip"=>"15", "full-text"=>"15", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2016", "month"=>"1"}
  • {"unique-ip"=>"11", "full-text"=>"11", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2016", "month"=>"3"}
  • {"unique-ip"=>"8", "full-text"=>"9", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2016", "month"=>"4"}
  • {"unique-ip"=>"8", "full-text"=>"9", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"5"}
  • {"unique-ip"=>"10", "full-text"=>"6", "pdf"=>"19", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"6"}
  • {"unique-ip"=>"6", "full-text"=>"5", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"7"}
  • {"unique-ip"=>"13", "full-text"=>"17", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"8"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"9"}
  • {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"7", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
  • {"unique-ip"=>"9", "full-text"=>"9", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"11"}
  • {"unique-ip"=>"35", "full-text"=>"16", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"15", "supp-data"=>"1", "cited-by"=>"1", "year"=>"2016", "month"=>"12"}
  • {"unique-ip"=>"7", "full-text"=>"6", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"1"}
  • {"unique-ip"=>"10", "full-text"=>"8", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"10", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"2"}
  • {"unique-ip"=>"11", "full-text"=>"11", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"3"}
  • {"unique-ip"=>"10", "full-text"=>"9", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"4"}
  • {"unique-ip"=>"34", "full-text"=>"24", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"10", "supp-data"=>"1", "cited-by"=>"1", "year"=>"2017", "month"=>"5"}
  • {"unique-ip"=>"14", "full-text"=>"15", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"6"}
  • {"unique-ip"=>"16", "full-text"=>"16", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"7"}
  • {"unique-ip"=>"16", "full-text"=>"15", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"8"}
  • {"unique-ip"=>"14", "full-text"=>"13", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"9"}
  • {"unique-ip"=>"9", "full-text"=>"10", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"10"}
  • {"unique-ip"=>"9", "full-text"=>"9", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2017", "month"=>"11"}
  • {"unique-ip"=>"11", "full-text"=>"13", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"12"}
  • {"unique-ip"=>"14", "full-text"=>"13", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"1", "cited-by"=>"1", "year"=>"2018", "month"=>"1"}
  • {"unique-ip"=>"17", "full-text"=>"14", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
  • {"unique-ip"=>"51", "full-text"=>"54", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"1"}
  • {"unique-ip"=>"14", "full-text"=>"13", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
  • {"unique-ip"=>"23", "full-text"=>"32", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
  • {"unique-ip"=>"18", "full-text"=>"21", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
  • {"unique-ip"=>"14", "full-text"=>"14", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"1", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"20", "full-text"=>"21", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"1", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"67", "full-text"=>"81", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"54", "full-text"=>"65", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"45", "full-text"=>"44", "pdf"=>"10", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"117", "full-text"=>"125", "pdf"=>"10", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"59", "full-text"=>"60", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"40", "full-text"=>"43", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"1", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"44", "full-text"=>"50", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"96", "full-text"=>"95", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"127", "full-text"=>"131", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}

Relative Metric

{"start_date"=>"2014-01-01T00:00:00Z", "end_date"=>"2014-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences/Computational biology", "average_usage"=>[341, 529]}, {"subject_area"=>"/Computer and information sciences", "average_usage"=>[327, 511]}, {"subject_area"=>"/Computer and information sciences/Information technology", "average_usage"=>[314, 484]}, {"subject_area"=>"/Computer and information sciences/Network analysis", "average_usage"=>[347, 531]}, {"subject_area"=>"/Engineering and technology", "average_usage"=>[282]}, {"subject_area"=>"/Physical sciences", "average_usage"=>[271]}]}
Loading … Spinner
There are currently no alerts