Protein–Protein Interactions Essentials: Key Concepts to Building and Analyzing Interactome Networks
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{"title"=>"Protein-protein interactions essentials: Key concepts to building and analyzing interactome networks", "type"=>"journal", "authors"=>[{"first_name"=>"Javier", "last_name"=>"de Las Rivas", "scopus_author_id"=>"54790571800"}, {"first_name"=>"Celia", "last_name"=>"Fontanillo", "scopus_author_id"=>"25929779300"}], "year"=>2010, "source"=>"PLoS Computational Biology", "identifiers"=>{"pmid"=>"20589078", "doi"=>"10.1371/journal.pcbi.1000807", "sgr"=>"77955505357", "isbn"=>"1553-7358 (Electronic)\\r1553-734X (Linking)", "scopus"=>"2-s2.0-77955505357", "issn"=>"1553734X", "pui"=>"359337528"}, "id"=>"94826ee4-ffb1-34a0-8fb3-fe79a744ec9f", "abstract"=>"Decades of research into cell biology, molecular biology, biochemistry, structural biology, and biophysics have produced a remarkable compendium of knowledge on the function and molecular properties of individual proteins. This knowledge is well recorded and manually curated into major protein databases like UniProt [1], [2]. However, proteins rarely act alone. Many times they team up into “molecular machines” and have intricate physicochemical dynamic connections to undertake biological functions at both cellular and systems levels. A critical step towards unraveling the complex molecular relationships in living systems is the mapping of protein-to-protein physical “interactions”. The complete map of protein interactions that can occur in a living organism is called the interactome [3]. Interactome mapping has become one of the main scopes of current biological research, similar to the way “genome” projects were a driving force of molecular biology 20 years ago.", "link"=>"http://www.mendeley.com/research/proteinprotein-interactions-essentials-key-concepts-building-analyzing-interactome-networks", "reader_count"=>605, "reader_count_by_academic_status"=>{"Unspecified"=>9, "Professor > Associate Professor"=>25, "Student > Doctoral Student"=>22, "Researcher"=>111, "Student > Ph. D. Student"=>187, "Student > Postgraduate"=>31, "Student > Master"=>105, "Other"=>19, "Student > Bachelor"=>69, "Lecturer"=>6, "Lecturer > Senior Lecturer"=>5, "Professor"=>16}, "reader_count_by_user_role"=>{"Unspecified"=>9, "Professor > Associate Professor"=>25, "Student > Doctoral Student"=>22, "Researcher"=>111, "Student > Ph. D. Student"=>187, "Student > Postgraduate"=>31, "Student > Master"=>105, "Other"=>19, "Student > Bachelor"=>69, "Lecturer"=>6, "Lecturer > Senior Lecturer"=>5, "Professor"=>16}, "reader_count_by_subject_area"=>{"Unspecified"=>16, "Agricultural and Biological Sciences"=>317, "Business, Management and Accounting"=>1, "Chemical Engineering"=>1, "Chemistry"=>46, "Computer Science"=>70, "Engineering"=>18, "Biochemistry, Genetics and Molecular Biology"=>87, "Mathematics"=>6, "Medicine and Dentistry"=>16, "Neuroscience"=>6, "Design"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>6, "Physics and Astronomy"=>6, "Social Sciences"=>2, "Immunology and Microbiology"=>4, "Linguistics"=>1, "Environmental Science"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>16}, "Social Sciences"=>{"Social Sciences"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>6}, "Mathematics"=>{"Mathematics"=>6}, "Unspecified"=>{"Unspecified"=>16}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>6}, "Environmental Science"=>{"Environmental Science"=>1}, "Chemical Engineering"=>{"Chemical Engineering"=>1}, "Design"=>{"Design"=>1}, "Engineering"=>{"Engineering"=>18}, "Chemistry"=>{"Chemistry"=>46}, "Neuroscience"=>{"Neuroscience"=>6}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>4}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>317}, "Computer Science"=>{"Computer Science"=>70}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Linguistics"=>{"Linguistics"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>87}}, "reader_count_by_country"=>{"United States"=>10, "Portugal"=>1, "Russia"=>1, "South Korea"=>2, "Netherlands"=>1, "Korea (South)"=>1, "Luxembourg"=>1, "China"=>1, "Brazil"=>3, "Poland"=>2, "Slovenia"=>2, "France"=>3, "Colombia"=>3, "Argentina"=>2, "Hungary"=>2, "Japan"=>4, "United Kingdom"=>11, "Switzerland"=>1, "India"=>6, "Spain"=>3, "Canada"=>2, "Czech Republic"=>1, "Turkey"=>2, "Norway"=>1, "South Africa"=>1, "Italy"=>3, "Mexico"=>2, "Australia"=>1, "Germany"=>8}, "group_count"=>24}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/843018"], "description"=>"<p>The two most widely used experimental proteomic techniques applied to measure PPIs are yeast two-hybrid (Y2H) and tandem affinity purification coupled to mass spectrometry (TAP-MS); the former technique is a binary method (which measures physical direct interactions between protein pairs), and the latter a co-complex method (which measures physical interactions between groups of proteins without distinguishing whether they are direct or indirect). The interactions shown in the left panel (green links) correspond to the true interactions existing between two groups of proteins (set <b>A</b> with four proteins and set <b>B</b> with three proteins). The interactions shown in the right panels correspond to the networks derived from the experimentally measured interactions existing between the six proteins analyzed: the network in the top right panel (blue links) presents the interactions obtained using a binary method; the network in the bottom right panel (red links) presents the interactions obtained using a co-complex method. The red links are calculated applying the spoke model to the TAP-MS experimental data, but three of the interactions deduced (links with an X) do not occur.</p>", "links"=>[], "tags"=>["methods", "co-complex", "approaches"], "article_id"=>513477, "categories"=>["Medicine", "Biochemistry", "Molecular Biology", "Biophysics"], "users"=>["Javier De Las Rivas", "Celia Fontanillo"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000807.g001", "stats"=>{"downloads"=>0, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Binary_methods_and_co_complex_methods_two_approaches_to_determine_PPIs_/513477", "title"=>"Binary methods and co-complex methods: two approaches to determine PPIs.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 00:48:34"}
  • {"files"=>["https://ndownloader.figshare.com/files/843309"], "description"=>"<p>The table divided in three sections: <b>primary databases</b>, which include PPIs from large- and small-scale (Lsc & Ssc) experimental data that are usually obtained from curation of research articles (8 resources included: BIND, BioGRID, DIP, HPRD, IntAct, MINT, MIPS-MPACT, MIPS-MPPI); <b>meta-databases</b>, which include PPIs derived from integration and unification of several primary repositories (3 resources: APID, MPIDB, PINA); <b>prediction databases</b>, which include PPIs from experimental analyses together with predicted PPIs obtained from the analyses of heterogenous biological data (5 resources: MiMI, PIPs, OPHID, STRING, UniHI). The table shows the total number of proteins and interactions that were reported by each repository in December 2009 (as far as we could see in the respective Web site). The numbers are in brackets [ ] when the repository includes PPIs and other types of interactions (e.g., protein-ligand interactions or for the case of prediction databases nonPPI data). The question mark [?] indicates that the number of distinct proteins included is such repository could not be found in the Web.</p>", "links"=>[], "tags"=>["ppi", "databases"], "article_id"=>513775, "categories"=>["Medicine", "Biochemistry", "Molecular Biology", "Biophysics"], "users"=>["Javier De Las Rivas", "Celia Fontanillo"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000807.t001", "stats"=>{"downloads"=>7, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Description_of_PPI_databases_and_repositories_/513775", "title"=>"Description of PPI databases and repositories.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-21 00:50:13"}
  • {"files"=>["https://ndownloader.figshare.com/files/843232"], "description"=>"<p>Comparison between a known pathway (NOTCH signaling pathway, taken from the KEGG database, ID: hsa04330) and the corresponding interactome network build using the proteins that interact with human NOTCH proteins. The top panel (<b>A</b>) shows the pathway including nine proteins (green boxes) directly connected to NOTCH. In this pathway, the central element is the NOTCH receptor and the interaction of its intracellular domain (called NICD) with protein RBPJ. The bottom panel (<b>B</b>) shows the NOTCH PPI network (built with Cytoscape and APID2NET), including all interactors proven with at least two different experiments. The number of experiments is indicated next to each link (blue line). The PPI network provides complementry information to the KEGG pathway, revealing the particular links of each of the four NOTCH paralogous proteins (NOTCH1, 2, 3, and 4) present in the human proteome. The biomolecular elements included in both networks are quite similar and the information that can be deduced from them is complementary. This can be seen in the interaction between NOTCH and RBPJ that drives the central signaling of the pathway and it is present in both networks.</p>", "links"=>[], "tags"=>["derived", "ppis", "compared", "canonical"], "article_id"=>513697, "categories"=>["Medicine", "Biochemistry", "Molecular Biology", "Biophysics"], "users"=>["Javier De Las Rivas", "Celia Fontanillo"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000807.g003", "stats"=>{"downloads"=>3, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_network_derived_from_PPIs_compared_to_the_related_canonical_pathway_/513697", "title"=>"A network derived from PPIs compared to the related canonical pathway.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 00:49:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/843122"], "description"=>"<p>Analysis of human interactome PPI data showing the coverage of six major primary databases (BIND, BioGRID, DIP, HPRD, IntAct, and MINT), according to the integration provided by the meta-database APID. (<b>A</b>) Growth of the total number of human PPIs during the last 3 years. (<b>B</b>) Number of PPIs obtained from each primary repository showing the % (with respect to the total number of PPIs: 80,032 in December 2009) and the number of PPIs only reported by each database (shown inside the corresponding sector of the Venn diagram). Coverage and intersection of PPIs with 3-D structural information: (<b>C</b>) Intersection between the PPIs of all human proteins that have at least one <i>Pfam</i> annotated (69,079 interactions, called <i>ppihs_all</i>) and the PPIs that include proteins with 3-D structural information (9,879 interactions, called <i>ppihsxsdd</i>); (<b>D</b>) intersection between the PPIs with 3-D structural information and a more stringent interactome constituted by PPIs proven at least by two experimental methods (16,959 interactions, called <i>ppihsx2meth</i>); (<b>E</b>) intersection between the PPIs with 3-D structural information and more stringent interactome constituted by interactions between proteins that are annotated to the same KEGG functional pathway (7,693 interactions, called <i>ppihsxKEGG</i>).</p>", "links"=>[], "tags"=>["overlap", "databases", "3-d"], "article_id"=>513583, "categories"=>["Medicine", "Biochemistry", "Molecular Biology", "Biophysics"], "users"=>["Javier De Las Rivas", "Celia Fontanillo"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000807.g002", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Human_interactome_overlap_of_six_databases_and_coverage_of_3_D_structural_data_/513583", "title"=>"Human interactome: overlap of six databases and coverage of 3-D structural data.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 00:49:10"}

PMC Usage Stats | Further Information

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  • {"month"=>"11", "scanned-page-browse"=>"0", "cited-by"=>"0", "abstract"=>"0", "full-text"=>"46", "year"=>"2010", "pdf"=>"36", "unique-ip"=>"43", "figure"=>"15", "scanned-summary"=>"0", "supp-data"=>"0"}
  • {"scanned-page-browse"=>"0", "month"=>"12", "cited-by"=>"0", "abstract"=>"0", "full-text"=>"47", "unique-ip"=>"43", "pdf"=>"26", "year"=>"2010", "figure"=>"7", "scanned-summary"=>"0", "supp-data"=>"0"}
  • {"month"=>"1", "scanned-page-browse"=>"0", "cited-by"=>"0", "abstract"=>"0", "full-text"=>"74", "year"=>"2011", "pdf"=>"37", "unique-ip"=>"66", "figure"=>"14", "scanned-summary"=>"0", "supp-data"=>"0"}
  • {"scanned-page-browse"=>"0", "month"=>"2", "cited-by"=>"0", "abstract"=>"0", "full-text"=>"78", "unique-ip"=>"51", "pdf"=>"25", "year"=>"2011", "figure"=>"16", "scanned-summary"=>"0", "supp-data"=>"0"}
  • {"month"=>"3", "scanned-page-browse"=>"0", "cited-by"=>"0", "abstract"=>"0", "full-text"=>"163", "year"=>"2011", "pdf"=>"52", "unique-ip"=>"112", "figure"=>"17", "scanned-summary"=>"0", "supp-data"=>"0"}
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  • {"month"=>"7", "scanned-page-browse"=>"0", "cited-by"=>"0", "abstract"=>"0", "full-text"=>"24", "year"=>"2011", "pdf"=>"13", "unique-ip"=>"18", "figure"=>"2", "scanned-summary"=>"0", "supp-data"=>"0"}
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  • {"month"=>"11", "scanned-page-browse"=>"0", "cited-by"=>"0", "abstract"=>"0", "full-text"=>"87", "year"=>"2011", "pdf"=>"37", "unique-ip"=>"79", "figure"=>"20", "scanned-summary"=>"0", "supp-data"=>"0"}
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  • {"month"=>"2", "scanned-page-browse"=>"0", "cited-by"=>"0", "abstract"=>"0", "full-text"=>"67", "year"=>"2012", "pdf"=>"37", "unique-ip"=>"59", "figure"=>"13", "scanned-summary"=>"0", "supp-data"=>"0"}
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  • {"unique-ip"=>"65", "full-text"=>"80", "pdf"=>"26", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"13", "supp-data"=>"0", "cited-by"=>"2", "year"=>"2012", "month"=>"9"}
  • {"unique-ip"=>"77", "full-text"=>"80", "pdf"=>"23", "abstract"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"9", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2012", "month"=>"10"}
  • {"unique-ip"=>"51", "full-text"=>"50", "pdf"=>"19", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"15", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2012", "month"=>"12"}
  • {"unique-ip"=>"56", "full-text"=>"70", "pdf"=>"14", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"7", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2013", "month"=>"1"}
  • {"unique-ip"=>"72", "full-text"=>"79", "pdf"=>"15", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2013", "month"=>"2"}
  • {"unique-ip"=>"78", "full-text"=>"94", "pdf"=>"17", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"6", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2013", "month"=>"3"}
  • {"unique-ip"=>"66", "full-text"=>"79", "pdf"=>"15", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"6", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"4"}
  • {"unique-ip"=>"66", "full-text"=>"77", "pdf"=>"23", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"12", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2012", "month"=>"11"}
  • {"unique-ip"=>"77", "full-text"=>"85", "pdf"=>"20", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"8", "supp-data"=>"0", "cited-by"=>"2", "year"=>"2013", "month"=>"5"}
  • {"unique-ip"=>"42", "full-text"=>"46", "pdf"=>"194", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2013", "month"=>"6"}
  • {"unique-ip"=>"54", "full-text"=>"54", "pdf"=>"47", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"12", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"7"}
  • {"unique-ip"=>"55", "full-text"=>"94", "pdf"=>"18", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"11", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"8"}
  • {"unique-ip"=>"60", "full-text"=>"100", "pdf"=>"11", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"9"}
  • {"unique-ip"=>"44", "full-text"=>"42", "pdf"=>"13", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"9", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"10"}
  • {"unique-ip"=>"42", "full-text"=>"48", "pdf"=>"9", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2013", "month"=>"11"}
  • {"unique-ip"=>"41", "full-text"=>"44", "pdf"=>"9", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"13", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"12"}
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  • {"unique-ip"=>"40", "full-text"=>"48", "pdf"=>"18", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"3"}
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Relative Metric

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