SMETANA: Accurate and Scalable Algorithm for Probabilistic Alignment of Large-Scale Biological Networks
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{"title"=>"SMETANA: Accurate and Scalable Algorithm for Probabilistic Alignment of Large-Scale Biological Networks", "type"=>"journal", "authors"=>[{"first_name"=>"Sayed Mohammad Ebrahim", "last_name"=>"Sahraeian", "scopus_author_id"=>"18042359100"}, {"first_name"=>"Byung Jun", "last_name"=>"Yoon", "scopus_author_id"=>"7201805669"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84880057180", "doi"=>"10.1371/journal.pone.0067995", "pui"=>"369305094", "issn"=>"19326203", "pmid"=>"23874484", "scopus"=>"2-s2.0-84880057180"}, "id"=>"6f0424cb-052f-3587-80c6-0922d6d3236f", "abstract"=>"In this paper we introduce an efficient algorithm for alignment of multiple large-scale biological networks. In this scheme, we first compute a probabilistic similarity measure between nodes that belong to different networks using a semi-Markov random walk model. The estimated probabilities are further enhanced by incorporating the local and the cross-species network similarity information through the use of two different types of probabilistic consistency transformations. The transformed alignment probabilities are used to predict the alignment of multiple networks based on a greedy approach. We demonstrate that the proposed algorithm, called SMETANA, outperforms many state-of-the-art network alignment techniques, in terms of computational efficiency, alignment accuracy, and scalability. Our experiments show that SMETANA can easily align tens of genome-scale networks with thousands of nodes on a personal computer without any difficulty. The source code of SMETANA is available upon request. The source code of SMETANA can be downloaded from http://www.ece.tamu.edu/~bjyoon/SMETANA/.", "link"=>"http://www.mendeley.com/research/smetana-accurate-scalable-algorithm-probabilistic-alignment-largescale-biological-networks", "reader_count"=>27, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>3, "Researcher"=>5, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>11, "Student > Postgraduate"=>1, "Student > Master"=>3}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>3, "Researcher"=>5, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>11, "Student > Postgraduate"=>1, "Student > Master"=>3}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Unspecified"=>1, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>4, "Mathematics"=>1, "Agricultural and Biological Sciences"=>9, "Computer Science"=>9, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>9}, "Computer Science"=>{"Computer Science"=>9}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>4}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>1}, "Environmental Science"=>{"Environmental Science"=>1}}, "reader_count_by_country"=>{"United States"=>1, "Brazil"=>1, "Slovenia"=>1}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1118200"], "description"=>"<p>(A) Equivalence class coverage: Number of equivalence classes in the 5-way alignment experiment that contain nodes from species (). (B) Node Coverage: Number of nodes (i.e. proteins) that belong to equivalence classes that contain nodes from species in the 5-way alignment.</p>", "links"=>[], "tags"=>["Biochemistry", "proteins", "Protein interactions", "Computational biology", "genomics", "Genome analysis tools", "Genetic networks", "Comparative genomics", "systems biology", "algorithms", "Applied mathematics", "alignment"], "article_id"=>744852, "categories"=>["Information And Computing Sciences", "Mathematics", "Biological Sciences"], "users"=>["Sayed Mohammad Ebrahim Sahraeian", "Byung-Jun Yoon"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0067995.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Performance_of_various_network_alignment_algorithms_/744852", "title"=>"Performance of various network alignment algorithms.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-12 01:30:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1118202"], "description"=>"<p>(A) Equivalence class coverage: Number of equivalence classes in the 8-way alignment experiment that contain nodes from species (). (B) Node Coverage: Number of nodes (i.e. proteins) that belong to equivalence classes that contain nodes from species in the 8-way alignment.</p>", "links"=>[], "tags"=>["Biochemistry", "proteins", "Protein interactions", "Computational biology", "genomics", "Genome analysis tools", "Genetic networks", "Comparative genomics", "systems biology", "algorithms", "Applied mathematics", "alignment"], "article_id"=>744854, "categories"=>["Information And Computing Sciences", "Mathematics", "Biological Sciences"], "users"=>["Sayed Mohammad Ebrahim Sahraeian", "Byung-Jun Yoon"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0067995.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Performance_of_various_network_alignment_algorithms_/744854", "title"=>"Performance of various network alignment algorithms.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-12 01:30:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1118204"], "description"=>"<p>CI reports the total number of conserved edges between any of the equivalence classes in the alignment. COI reports the total number of conserved edges between “correct” equivalence classes that consist of orthologous nodes.</p>", "links"=>[], "tags"=>["Biochemistry", "proteins", "Protein interactions", "Computational biology", "genomics", "Genome analysis tools", "Genetic networks", "Comparative genomics", "systems biology", "algorithms", "Applied mathematics", "conserved", "interactions", "orthologous"], "article_id"=>744855, "categories"=>["Information And Computing Sciences", "Mathematics", "Biological Sciences"], "users"=>["Sayed Mohammad Ebrahim Sahraeian", "Byung-Jun Yoon"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0067995.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Number_of_conserved_interactions_CI_and_conserved_orthologous_interactions_COI_for_different_alignments_/744855", "title"=>"Number of conserved interactions (CI) and conserved orthologous interactions (COI) for different alignments.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-12 01:30:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1118206"], "description"=>"<p>The alignment performance has been estimated at several different levels of separation between the similarity score distribution for orthologous node pairs and that for non-orthologs pairs. Increasing the bias increases the separation between the two score distributions, which increases the discriminative power of the node similarity score for predicting potential orthologs. Measures reported: specificity (SPE), number of correct nodes (CN) (which reflects the sensitivity), mean normalized entropy (MNE), number of conserved interactions (CI), number of conserved orthologous interactions (COI).</p>", "links"=>[], "tags"=>["Biochemistry", "proteins", "Protein interactions", "Computational biology", "genomics", "Genome analysis tools", "Genetic networks", "Comparative genomics", "systems biology", "algorithms", "Applied mathematics", "node", "alignment"], "article_id"=>744857, "categories"=>["Information And Computing Sciences", "Mathematics", "Biological Sciences"], "users"=>["Sayed Mohammad Ebrahim Sahraeian", "Byung-Jun Yoon"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0067995.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effects_of_node_similarity_on_the_performance_of_different_network_alignment_algorithms_/744857", "title"=>"Effects of node similarity on the performance of different network alignment algorithms.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-12 01:30:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1118208"], "description"=>"<p>The total CPU time for the pairwise, 5-way, and 8-way alignments. CPU time has been averaged over DMC, DMR, and CG datasets (measured in seconds).</p>", "links"=>[], "tags"=>["Biochemistry", "proteins", "Protein interactions", "Computational biology", "genomics", "Genome analysis tools", "Genetic networks", "Comparative genomics", "systems biology", "algorithms", "Applied mathematics", "cpu", "aligning"], "article_id"=>744859, "categories"=>["Information And Computing Sciences", "Mathematics", "Biological Sciences"], "users"=>["Sayed Mohammad Ebrahim Sahraeian", "Byung-Jun Yoon"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0067995.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Total_CPU_time_for_aligning_the_networks_/744859", "title"=>"Total CPU time for aligning the networks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-12 01:30:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1118209"], "description"=>"<p>The trend of change in sensitivity (SEN) and specificity (SP) as the number of networks in the alignment increases for different multiple network alignment algorithms.</p>", "links"=>[], "tags"=>["Biochemistry", "proteins", "Protein interactions", "Computational biology", "genomics", "Genome analysis tools", "Genetic networks", "Comparative genomics", "systems biology", "algorithms", "Applied mathematics"], "article_id"=>744860, "categories"=>["Information And Computing Sciences", "Mathematics", "Biological Sciences"], "users"=>["Sayed Mohammad Ebrahim Sahraeian", "Byung-Jun Yoon"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0067995.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Performance_on_real_networks_/744860", "title"=>"Performance on real networks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-12 01:30:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1118211"], "description"=>"<p>(A) Transcription factor. (B) Replication factor C. (C) RNA polymerase. (D) DNA replication. (Aligned nodes are placed in the same row of alignment and connected with yellow dashed lines. In each network, the interaction in the IsoBase dataset is shown in solid lines. For <i>D. melanogaster</i> some edges which are missed in IsoBase but are present in STRING protein interaction database <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067995#pone.0067995-Szklarczyk1\" target=\"_blank\">[52]</a> is shown in dotted gray lines).</p>", "links"=>[], "tags"=>["Biochemistry", "proteins", "Protein interactions", "Computational biology", "genomics", "Genome analysis tools", "Genetic networks", "Comparative genomics", "systems biology", "algorithms", "Applied mathematics", "subnetwork", "regions", "3-way", "alignment"], "article_id"=>744862, "categories"=>["Information And Computing Sciences", "Mathematics", "Biological Sciences"], "users"=>["Sayed Mohammad Ebrahim Sahraeian", "Byung-Jun Yoon"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0067995.g007"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Conserved_subnetwork_regions_in_the_3_way_alignment_of_D_melanogaster_H_sapiens_and_S_cerevisiae_using_the_proposed_method_/744862", "title"=>"Conserved subnetwork regions in the 3-way alignment of <i>D. melanogaster</i>, <i>H. sapiens</i>, and <i>S. cerevisiae</i> using the proposed method.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-12 01:30:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1118212"], "description"=>"<p>Performance comparison based on the pairwise alignment of two networks of size 3,000 and 4,000. The performance of each method is assessed using the following metrics: specificity (SP), number of correct nodes (CN), and mean normalized entropy (MNE). In each column, best performance is shown in bold.</p>", "links"=>[], "tags"=>["Biochemistry", "proteins", "Protein interactions", "Computational biology", "genomics", "Genome analysis tools", "Genetic networks", "Comparative genomics", "systems biology", "algorithms", "Applied mathematics", "pairwise"], "article_id"=>744863, "categories"=>["Information And Computing Sciences", "Mathematics", "Biological Sciences"], "users"=>["Sayed Mohammad Ebrahim Sahraeian", "Byung-Jun Yoon"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0067995.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Performance_of_different_algorithms_for_pairwise_network_alignment_/744863", "title"=>"Performance of different algorithms for pairwise network alignment.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-12 01:30:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1118213"], "description"=>"<p>Performance comparison based on the 5-way alignment of five networks of size 1500, 2000, 2500, 3000 and 3000. The last three rows are obtained by considering only equivalence classes that contain at least one node from every species. The performance of each method is assessed using the following metrics: specificity (SP), number of correct nodes (CN), and mean normalized entropy (MNE). In each metrics, best performance is shown in bold.</p>", "links"=>[], "tags"=>["Biochemistry", "proteins", "Protein interactions", "Computational biology", "genomics", "Genome analysis tools", "Genetic networks", "Comparative genomics", "systems biology", "algorithms", "Applied mathematics", "5-way"], "article_id"=>744864, "categories"=>["Information And Computing Sciences", "Mathematics", "Biological Sciences"], "users"=>["Sayed Mohammad Ebrahim Sahraeian", "Byung-Jun Yoon"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0067995.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Performance_of_different_algorithms_for_5_way_network_alignment_/744864", "title"=>"Performance of different algorithms for 5-way network alignment.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-12 01:30:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1118215"], "description"=>"<p>Performance comparison based on the 8-way alignment of eight networks of equal size 1,000. The last three rows are obtained by considering only equivalence classes that contain at least one node from every species. The performance of each method is assessed using the following metrics: specificity(SP), number of correct nodes (CN), and mean normalized entropy (MNE). In each column, best performance is shown in bold.</p>", "links"=>[], "tags"=>["Biochemistry", "proteins", "Protein interactions", "Computational biology", "genomics", "Genome analysis tools", "Genetic networks", "Comparative genomics", "systems biology", "algorithms", "Applied mathematics", "8-way"], "article_id"=>744866, "categories"=>["Information And Computing Sciences", "Mathematics", "Biological Sciences"], "users"=>["Sayed Mohammad Ebrahim Sahraeian", "Byung-Jun Yoon"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0067995.t003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Performance_of_different_algorithms_for_8_way_network_alignment_/744866", "title"=>"Performance of different algorithms for 8-way network alignment.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-12 01:30:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1118216"], "description"=>"<div><p>In this paper we introduce an efficient algorithm for alignment of multiple large-scale biological networks. In this scheme, we first compute a probabilistic similarity measure between nodes that belong to different networks using a semi-Markov random walk model. The estimated probabilities are further enhanced by incorporating the local and the cross-species network similarity information through the use of two different types of probabilistic consistency transformations. The transformed alignment probabilities are used to predict the alignment of multiple networks based on a greedy approach. We demonstrate that the proposed algorithm, called SMETANA, outperforms many state-of-the-art network alignment techniques, in terms of computational efficiency, alignment accuracy, and scalability. Our experiments show that SMETANA can easily align tens of genome-scale networks with thousands of nodes on a personal computer without any difficulty. The source code of SMETANA is available upon request. The source code of SMETANA can be downloaded from <a href=\"http://www.ece.tamu.edu/~bjyoon/SMETANA/\" target=\"_blank\">http://www.ece.tamu.edu/~bjyoon/SMETANA/</a>.</p></div>", "links"=>[], "tags"=>["Biochemistry", "proteins", "Protein interactions", "Computational biology", "genomics", "Genome analysis tools", "Genetic networks", "Comparative genomics", "systems biology", "algorithms", "Applied mathematics", "scalable", "algorithm", "probabilistic", "alignment", "large-scale"], "article_id"=>744867, "categories"=>["Information And Computing Sciences", "Mathematics", "Biological Sciences"], "users"=>["Sayed Mohammad Ebrahim Sahraeian", "Byung-Jun Yoon"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0067995"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_SMETANA_Accurate_and_Scalable_Algorithm_for_Probabilistic_Alignment_of_Large_Scale_Biological_Networks_/744867", "title"=>"SMETANA: Accurate and Scalable Algorithm for Probabilistic Alignment of Large-Scale Biological Networks", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-12 01:30:24"}

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

Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[269, 466, 588, 697, 800, 896, 988, 1076, 1165, 1254, 1340, 1417]}, {"subject_area"=>"/Biology and life sciences/Biochemistry", "average_usage"=>[266, 468, 593, 703, 804, 903, 993, 1084, 1171, 1256, 1339, 1422, 1492]}, {"subject_area"=>"/Biology and life sciences/Genetics", "average_usage"=>[284, 491, 620, 738, 843, 945, 1043, 1137, 1225, 1315, 1400, 1479, 1555]}, {"subject_area"=>"/Computer and information sciences/Network analysis", "average_usage"=>[340, 548, 701, 844, 945, 1073, 1189, 1282, 1391, 1488, 1562, 1660, 1731]}, {"subject_area"=>"/Physical sciences/Mathematics", "average_usage"=>[259, 431, 541, 639, 727, 816, 898, 980, 1061, 1136, 1214, 1294, 1356]}]}
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