Multi-Dimensional Prioritization of Dental Caries Candidate Genes and Its Enriched Dense Network Modules
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{"title"=>"Multi-Dimensional Prioritization of Dental Caries Candidate Genes and Its Enriched Dense Network Modules", "type"=>"journal", "authors"=>[{"first_name"=>"Quan", "last_name"=>"Wang", "scopus_author_id"=>"57188732177"}, {"first_name"=>"Peilin", "last_name"=>"Jia", "scopus_author_id"=>"14030192100"}, {"first_name"=>"Karen T.", "last_name"=>"Cuenco", "scopus_author_id"=>"6506157707"}, {"first_name"=>"Eleanor", "last_name"=>"Feingold", "scopus_author_id"=>"7006820121"}, {"first_name"=>"Mary L.", "last_name"=>"Marazita", "scopus_author_id"=>"7006257137"}, {"first_name"=>"Lily", "last_name"=>"Wang", "scopus_author_id"=>"35293641400"}, {"first_name"=>"Zhongming", "last_name"=>"Zhao", "scopus_author_id"=>"7404147874"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"370004555", "issn"=>"19326203", "isbn"=>"1932-6203 (Electronic)\r1932-6203 (Linking)", "doi"=>"10.1371/journal.pone.0076666", "scopus"=>"2-s2.0-84885414503", "pmid"=>"24146904", "sgr"=>"84885414503"}, "id"=>"0ce8c680-a3a5-3ec6-af88-ea6dd7b90292", "abstract"=>"A number of genetic studies have suggested numerous susceptibility genes for dental caries over the past decade with few definite conclusions. The rapid accumulation of relevant information, along with the complex architecture of the disease, provides a challenging but also unique opportunity to review and integrate the heterogeneous data for follow-up validation and exploration. In this study, we collected and curated candidate genes from four major categories: association studies, linkage scans, gene expression analyses, and literature mining. Candidate genes were prioritized according to the magnitude of evidence related to dental caries. We then searched for dense modules enriched with the prioritized candidate genes through their protein-protein interactions (PPIs). We identified 23 modules comprising of 53 genes. Functional analyses of these 53 genes revealed three major clusters: cytokine network relevant genes, matrix metalloproteinases (MMPs) family, and transforming growth factor-beta (TGF-β) family, all of which have been previously implicated to play important roles in tooth development and carious lesions. Through our extensive data collection and an integrative application of gene prioritization and PPI network analyses, we built a dental caries-specific sub-network for the first time. Our study provided insights into the molecular mechanisms underlying dental caries. The framework we proposed in this work can be applied to other complex diseases.", "link"=>"http://www.mendeley.com/research/multidimensional-prioritization-dental-caries-candidate-genes-enriched-dense-network-modules", "reader_count"=>21, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Student > Doctoral Student"=>2, "Researcher"=>3, "Student > Ph. D. Student"=>3, "Student > Postgraduate"=>3, "Student > Master"=>3, "Student > Bachelor"=>3, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Student > Doctoral Student"=>2, "Researcher"=>3, "Student > Ph. D. Student"=>3, "Student > Postgraduate"=>3, "Student > Master"=>3, "Student > Bachelor"=>3, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Engineering"=>1, "Biochemistry, Genetics and Molecular Biology"=>1, "Medicine and Dentistry"=>11, "Agricultural and Biological Sciences"=>4, "Social Sciences"=>1, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>11}, "Social Sciences"=>{"Social Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>4}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Unspecified"=>{"Unspecified"=>2}}, "reader_count_by_country"=>{"United States"=>1}, "group_count"=>0}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1234404"], "description"=>"<p>First, the biological knowledgebase BioGraph <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076666#pone.0076666-Liekens1\" target=\"_blank\">[34]</a> was explored to identify training gene set, and candidate genes were collected from previous studies and publications. We obtained 11 training genes and 1214 candidate genes in this data collection step. Second, a computational method ENDEAVOUR <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076666#pone.0076666-Aerts1\" target=\"_blank\">[13]</a> was utilized to prioritize the candidate genes. In this step, a ranked list of 960 candidate genes that could be recognized by ENDEAVOUR was generated. Third, dmGWAS <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076666#pone.0076666-Jia2\" target=\"_blank\">[33]</a> was employed to search for the dense modules upon human protein-protein interaction (PPI) network collected by Protein Interaction Network Analysis (PINA) platform <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076666#pone.0076666-Wu1\" target=\"_blank\">[53]</a>. This resulted in 469 dense modules. Finally, the 469 modules were evaluated and the top 23 ones were selected as promising modules.</p>", "links"=>[], "tags"=>["workflow"], "article_id"=>821112, "categories"=>["Information And Computing Sciences", "Biological Sciences"], "users"=>["Quan Wang", "Peilin Jia", "Karen T. Cuenco", "Eleanor Feingold", "Mary L. Marazita", "Lily Wang", "Zhongming Zhao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0076666.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_workflow_of_this_study_/821112", "title"=>"The workflow of this study.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-11 03:56:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1234406"], "description"=>"<p>Overlap of candidate genes between four categories.</p>", "links"=>[], "tags"=>["genes"], "article_id"=>821114, "categories"=>["Information And Computing Sciences", "Biological Sciences"], "users"=>["Quan Wang", "Peilin Jia", "Karen T. Cuenco", "Eleanor Feingold", "Mary L. Marazita", "Lily Wang", "Zhongming Zhao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0076666.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overlap_of_candidate_genes_between_four_categories_/821114", "title"=>"Overlap of candidate genes between four categories.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-11 03:56:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1234407"], "description"=>"<p>Three gene clusters with plausible functions were included: cytokine network relevant genes (<i>CCL2, CCL5, CCL8, CCL3, CXCL1, CXCL5, CCL7, CCL4, CCR5,</i> and <i>CCR10</i>), matrix metalloproteinases (MMPs) family genes (<i>MMP2, MMP3, MMP1,</i> and <i>MMP9</i>), and transforming growth factor-beta (TGF-β) family genes (<i>TGFB1, TGFBR2, TGFB2, TGFBR3,</i> and <i>TGFBR1</i>), all of which have been previously implicated to play important roles in tooth development and carious lesions.</p>", "links"=>[], "tags"=>["sub-network", "containing", "53", "dcgenes", "23", "modules", "generated"], "article_id"=>821115, "categories"=>["Information And Computing Sciences", "Biological Sciences"], "users"=>["Quan Wang", "Peilin Jia", "Karen T. Cuenco", "Eleanor Feingold", "Mary L. Marazita", "Lily Wang", "Zhongming Zhao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0076666.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_sub_network_containing_53_DCgenes_from_the_selected_23_modules_top_5_of_all_modules_generated_by_dmGWAS_/821115", "title"=>"The sub-network containing 53 DCgenes from the selected 23 modules (top 5% of all modules generated by dmGWAS).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-11 03:56:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1234409"], "description"=>"a<p>The total number is smaller than the sum of the four categories due to redundancy.</p>", "links"=>[], "tags"=>["caries", "genes"], "article_id"=>821117, "categories"=>["Information And Computing Sciences", "Biological Sciences"], "users"=>["Quan Wang", "Peilin Jia", "Karen T. Cuenco", "Eleanor Feingold", "Mary L. Marazita", "Lily Wang", "Zhongming Zhao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0076666.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Dental_caries_candidate_genes_in_four_categories_/821117", "title"=>"Dental caries candidate genes in four categories.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-10-11 03:56:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1234410"], "description"=>"a<p>The degree of a node is the number of its neighbors in the sub-network.</p>", "links"=>[], "tags"=>["53", "dcgenes", "residing", "23"], "article_id"=>821118, "categories"=>["Information And Computing Sciences", "Biological Sciences"], "users"=>["Quan Wang", "Peilin Jia", "Karen T. Cuenco", "Eleanor Feingold", "Mary L. Marazita", "Lily Wang", "Zhongming Zhao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0076666.t003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_53_DCgenes_residing_in_the_top_23_dense_modules_/821118", "title"=>"The 53 DCgenes residing in the top 23 dense modules.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-10-11 03:56:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1234411"], "description"=>"a<p>p-values computed by Fisher’s exact test.</p>b<p>The top 50 genes in the prioritized candidate gene list by ENDEAVOUR <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076666#pone.0076666-Aerts1\" target=\"_blank\">[13]</a>.</p>", "links"=>[], "tags"=>["ranked", "genes", "higher", "probability", "belonging"], "article_id"=>821119, "categories"=>["Information And Computing Sciences", "Biological Sciences"], "users"=>["Quan Wang", "Peilin Jia", "Karen T. Cuenco", "Eleanor Feingold", "Mary L. Marazita", "Lily Wang", "Zhongming Zhao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0076666.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_top_ranked_genes_have_a_higher_probability_of_belonging_to_multiple_categories_/821119", "title"=>"The top ranked genes have a higher probability of belonging to multiple categories.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-10-11 03:56:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/1234412"], "description"=>"<div><p>A number of genetic studies have suggested numerous susceptibility genes for dental caries over the past decade with few definite conclusions. The rapid accumulation of relevant information, along with the complex architecture of the disease, provides a challenging but also unique opportunity to review and integrate the heterogeneous data for follow-up validation and exploration. In this study, we collected and curated candidate genes from four major categories: association studies, linkage scans, gene expression analyses, and literature mining. Candidate genes were prioritized according to the magnitude of evidence related to dental caries. We then searched for dense modules enriched with the prioritized candidate genes through their protein-protein interactions (PPIs). We identified 23 modules comprising of 53 genes. Functional analyses of these 53 genes revealed three major clusters: cytokine network relevant genes, matrix metalloproteinases (MMPs) family, and transforming growth factor-beta (TGF-β) family, all of which have been previously implicated to play important roles in tooth development and carious lesions. Through our extensive data collection and an integrative application of gene prioritization and PPI network analyses, we built a dental caries-specific sub-network for the first time. Our study provided insights into the molecular mechanisms underlying dental caries. The framework we proposed in this work can be applied to other complex diseases.</p></div>", "links"=>[], "tags"=>["prioritization", "dental", "caries", "genes", "enriched"], "article_id"=>821120, "categories"=>["Information And Computing Sciences", "Biological Sciences"], "users"=>["Quan Wang", "Peilin Jia", "Karen T. Cuenco", "Eleanor Feingold", "Mary L. Marazita", "Lily Wang", "Zhongming Zhao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0076666"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Multi_Dimensional_Prioritization_of_Dental_Caries_Candidate_Genes_and_Its_Enriched_Dense_Network_Modules_/821120", "title"=>"Multi-Dimensional Prioritization of Dental Caries Candidate Genes and Its Enriched Dense Network Modules", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-10-11 03:56:24"}

PMC Usage Stats | Further Information

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Relative Metric

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