A Ten-MicroRNA Signature Identified from a Genome-Wide MicroRNA Expression Profiling in Human Epithelial Ovarian Cancer
Events
Loading … Spinner

Mendeley | Further Information

{"title"=>"A Ten-MicroRNA Signature Identified from a Genome-Wide MicroRNA Expression Profiling in Human Epithelial Ovarian Cancer", "type"=>"journal", "authors"=>[{"first_name"=>"Lin", "last_name"=>"Wang"}, {"first_name"=>"Miao-Jun", "last_name"=>"Zhu"}, {"first_name"=>"Ai-Min", "last_name"=>"Ren"}, {"first_name"=>"Hong-Fei", "last_name"=>"Wu"}, {"first_name"=>"Wu-Mei", "last_name"=>"Han"}, {"first_name"=>"Ruo-Ying", "last_name"=>"Tan"}, {"first_name"=>"Rui-Qin", "last_name"=>"Tu"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"doi"=>"10.1371/journal.pone.0096472", "pmid"=>"24816756", "issn"=>"1932-6203"}, "id"=>"7786d8d6-c9fd-3623-99ee-9c5c1232fddc", "abstract"=>"Epithelial ovarian cancer (EOC) is the most common gynecologic malignancy. To identify the micro-ribonucleic acids (miRNAs) expression profile in EOC tissues that may serve as a novel diagnostic biomarker for EOC detection, the expression of 1722 miRNAs from 15 normal ovarian tissue samples and 48 ovarian cancer samples was profiled by using a quantitative real-time polymerase chain reaction (qRT-PCR) assay. A ten-microRNA signature (hsa-miR-1271-5p, hsa-miR-574-3p, hsa-miR-182-5p, hsa-miR-183-5p, hsa-miR-96-5p, hsa-miR-15b-5p, hsa-miR-182-3p, hsa-miR-141-5p, hsa-miR-130b-5p, and hsa-miR-135b-3p) was identified to be able to distinguish human ovarian cancer tissues from normal tissues with 97% sensitivity and 92% specificity. Two miRNA clusters of miR183-96-183 (miR-96-5p, and miR-182, miR183) and miR200 (miR-141-5p, miR200a, b, c and miR429) are significantly up-regulated in ovarian cancer tissue samples compared to those of normal tissue samples, suggesting theses miRNAs may be involved in ovarian cancer development.", "link"=>"http://www.mendeley.com/research/tenmicrorna-signature-identified-genomewide-microrna-expression-profiling-human-epithelial-ovarian-c", "reader_count"=>23, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>1, "Student > Doctoral Student"=>2, "Researcher"=>5, "Student > Ph. D. Student"=>9, "Student > Postgraduate"=>2, "Student > Master"=>3, "Student > Bachelor"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>1, "Student > Doctoral Student"=>2, "Researcher"=>5, "Student > Ph. D. Student"=>9, "Student > Postgraduate"=>2, "Student > Master"=>3, "Student > Bachelor"=>1}, "reader_count_by_subject_area"=>{"Biochemistry, Genetics and Molecular Biology"=>3, "Agricultural and Biological Sciences"=>14, "Medicine and Dentistry"=>4, "Computer Science"=>1, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>4}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>14}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>3}}, "reader_count_by_country"=>{"Sweden"=>1, "United States"=>1, "India"=>1}, "group_count"=>1}

Scopus | Further Information

{"@_fa"=>"true", "link"=>[{"@_fa"=>"true", "@ref"=>"self", "@href"=>"https://api.elsevier.com/content/abstract/scopus_id/84901242702"}, {"@_fa"=>"true", "@ref"=>"author-affiliation", "@href"=>"https://api.elsevier.com/content/abstract/scopus_id/84901242702?field=author,affiliation"}, {"@_fa"=>"true", "@ref"=>"scopus", "@href"=>"https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84901242702&origin=inward"}, {"@_fa"=>"true", "@ref"=>"scopus-citedby", "@href"=>"https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=84901242702&origin=inward"}], "prism:url"=>"https://api.elsevier.com/content/abstract/scopus_id/84901242702", "dc:identifier"=>"SCOPUS_ID:84901242702", "eid"=>"2-s2.0-84901242702", "dc:title"=>"A ten-microRNA signature identified from a genome-wide microRNA expression profiling in human epithelial ovarian cancer", "dc:creator"=>"Wang L.", "prism:publicationName"=>"PLoS ONE", "prism:eIssn"=>"19326203", "prism:volume"=>"9", "prism:issueIdentifier"=>"5", "prism:pageRange"=>nil, "prism:coverDate"=>"2014-05-09", "prism:coverDisplayDate"=>"9 May 2014", "prism:doi"=>"10.1371/journal.pone.0096472", "citedby-count"=>"54", "affiliation"=>[{"@_fa"=>"true", "affilname"=>"Fudan University", "affiliation-city"=>"Shanghai", "affiliation-country"=>"China"}], "pubmed-id"=>"24816756", "prism:aggregationType"=>"Journal", "subtype"=>"ar", "subtypeDescription"=>"Article", "article-number"=>"e96472", "source-id"=>"10600153309", "openaccess"=>"1", "openaccessFlag"=>true}

Facebook

  • {"url"=>"http%3A%2F%2Fjournals.plos.org%2Fplosone%2Farticle%3Fid%3D10.1371%252Fjournal.pone.0096472", "share_count"=>0, "like_count"=>0, "comment_count"=>0, "click_count"=>0, "total_count"=>0}

Counter

  • {"month"=>"5", "year"=>"2014", "pdf_views"=>"58", "xml_views"=>"5", "html_views"=>"173"}
  • {"month"=>"6", "year"=>"2014", "pdf_views"=>"21", "xml_views"=>"1", "html_views"=>"95"}
  • {"month"=>"7", "year"=>"2014", "pdf_views"=>"34", "xml_views"=>"0", "html_views"=>"78"}
  • {"month"=>"8", "year"=>"2014", "pdf_views"=>"17", "xml_views"=>"2", "html_views"=>"53"}
  • {"month"=>"9", "year"=>"2014", "pdf_views"=>"12", "xml_views"=>"1", "html_views"=>"39"}
  • {"month"=>"10", "year"=>"2014", "pdf_views"=>"15", "xml_views"=>"2", "html_views"=>"47"}
  • {"month"=>"11", "year"=>"2014", "pdf_views"=>"11", "xml_views"=>"1", "html_views"=>"48"}
  • {"month"=>"12", "year"=>"2014", "pdf_views"=>"10", "xml_views"=>"1", "html_views"=>"30"}
  • {"month"=>"1", "year"=>"2015", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"42"}
  • {"month"=>"2", "year"=>"2015", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"21"}
  • {"month"=>"3", "year"=>"2015", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"33"}
  • {"month"=>"4", "year"=>"2015", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"28"}
  • {"month"=>"5", "year"=>"2015", "pdf_views"=>"14", "xml_views"=>"1", "html_views"=>"41"}
  • {"month"=>"6", "year"=>"2015", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"60"}
  • {"month"=>"7", "year"=>"2015", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"20"}
  • {"month"=>"8", "year"=>"2015", "pdf_views"=>"13", "xml_views"=>"0", "html_views"=>"43"}
  • {"month"=>"9", "year"=>"2015", "pdf_views"=>"9", "xml_views"=>"2", "html_views"=>"29"}
  • {"month"=>"10", "year"=>"2015", "pdf_views"=>"2", "xml_views"=>"0", "html_views"=>"30"}
  • {"month"=>"11", "year"=>"2015", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"32"}
  • {"month"=>"12", "year"=>"2015", "pdf_views"=>"9", "xml_views"=>"0", "html_views"=>"30"}
  • {"month"=>"1", "year"=>"2016", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"33"}
  • {"month"=>"2", "year"=>"2016", "pdf_views"=>"2", "xml_views"=>"0", "html_views"=>"20"}
  • {"month"=>"3", "year"=>"2016", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"30"}
  • {"month"=>"4", "year"=>"2016", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"33"}
  • {"month"=>"5", "year"=>"2016", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"25"}
  • {"month"=>"6", "year"=>"2016", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"32"}
  • {"month"=>"7", "year"=>"2016", "pdf_views"=>"10", "xml_views"=>"0", "html_views"=>"34"}
  • {"month"=>"8", "year"=>"2016", "pdf_views"=>"12", "xml_views"=>"0", "html_views"=>"17"}
  • {"month"=>"9", "year"=>"2016", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"23"}
  • {"month"=>"10", "year"=>"2016", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"16"}
  • {"month"=>"11", "year"=>"2016", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"32"}
  • {"month"=>"12", "year"=>"2016", "pdf_views"=>"25", "xml_views"=>"0", "html_views"=>"38"}
  • {"month"=>"1", "year"=>"2017", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"23"}
  • {"month"=>"2", "year"=>"2017", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"47"}
  • {"month"=>"3", "year"=>"2017", "pdf_views"=>"11", "xml_views"=>"2", "html_views"=>"57"}
  • {"month"=>"4", "year"=>"2017", "pdf_views"=>"16", "xml_views"=>"1", "html_views"=>"65"}
  • {"month"=>"5", "year"=>"2017", "pdf_views"=>"2", "xml_views"=>"0", "html_views"=>"17"}
  • {"month"=>"6", "year"=>"2017", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"34"}
  • {"month"=>"7", "year"=>"2017", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"33"}
  • {"month"=>"8", "year"=>"2017", "pdf_views"=>"2", "xml_views"=>"1", "html_views"=>"21"}
  • {"month"=>"9", "year"=>"2017", "pdf_views"=>"18", "xml_views"=>"0", "html_views"=>"37"}
  • {"month"=>"10", "year"=>"2017", "pdf_views"=>"2", "xml_views"=>"1", "html_views"=>"26"}
  • {"month"=>"11", "year"=>"2017", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"62"}
  • {"month"=>"12", "year"=>"2017", "pdf_views"=>"7", "xml_views"=>"2", "html_views"=>"35"}
  • {"month"=>"1", "year"=>"2018", "pdf_views"=>"0", "xml_views"=>"0", "html_views"=>"13"}
  • {"month"=>"2", "year"=>"2018", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"17"}
  • {"month"=>"3", "year"=>"2018", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"8"}
  • {"month"=>"4", "year"=>"2018", "pdf_views"=>"1", "xml_views"=>"0", "html_views"=>"15"}
  • {"month"=>"5", "year"=>"2018", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"20"}
  • {"month"=>"6", "year"=>"2018", "pdf_views"=>"13", "xml_views"=>"0", "html_views"=>"13"}
  • {"month"=>"7", "year"=>"2018", "pdf_views"=>"8", "xml_views"=>"3", "html_views"=>"12"}
  • {"month"=>"8", "year"=>"2018", "pdf_views"=>"5", "xml_views"=>"1", "html_views"=>"6"}
  • {"month"=>"9", "year"=>"2018", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"3"}
  • {"month"=>"10", "year"=>"2018", "pdf_views"=>"2", "xml_views"=>"1", "html_views"=>"11"}
  • {"month"=>"11", "year"=>"2018", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"5"}
  • {"month"=>"12", "year"=>"2018", "pdf_views"=>"1", "xml_views"=>"0", "html_views"=>"11"}
  • {"month"=>"1", "year"=>"2019", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"12"}
  • {"month"=>"2", "year"=>"2019", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"11"}
  • {"month"=>"3", "year"=>"2019", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"6"}
  • {"month"=>"4", "year"=>"2019", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"14"}
  • {"month"=>"5", "year"=>"2019", "pdf_views"=>"31", "xml_views"=>"0", "html_views"=>"10"}
  • {"month"=>"6", "year"=>"2019", "pdf_views"=>"10", "xml_views"=>"0", "html_views"=>"9"}
  • {"month"=>"7", "year"=>"2019", "pdf_views"=>"19", "xml_views"=>"0", "html_views"=>"7"}
  • {"month"=>"8", "year"=>"2019", "pdf_views"=>"19", "xml_views"=>"0", "html_views"=>"5"}
  • {"month"=>"9", "year"=>"2019", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"13"}
  • {"month"=>"10", "year"=>"2019", "pdf_views"=>"16", "xml_views"=>"0", "html_views"=>"11"}
  • {"month"=>"11", "year"=>"2019", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"9"}
  • {"month"=>"12", "year"=>"2019", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"3"}

Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1492066"], "description"=>"<p>OC =  Ovarian Cancer.</p><p>y =  years.</p><p>FIGO =  the TNM and International Federation of Gynecology and Obstetrics.</p><p>Adenocarcinoma NOS =  adenocarcinoma not otherwise specified.</p>", "links"=>[], "tags"=>["Computational biology", "genome analysis", "Transcriptome analysis", "Genome expression analysis", "genetics", "Cancer genetics", "genomics", "oncology", "Cancers and neoplasms", "Gynecological tumors", "Ovarian cancer", "Cancer detection and diagnosis", "Cancer risk factors"], "article_id"=>1022129, "categories"=>["Biological Sciences"], "users"=>["Lin Wang", "Miao-Jun Zhu", "Ai-Min Ren", "Hong-Fei Wu", "Wu-Mei Han", "Ruo-Ying Tan", "Rui-Qin Tu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096472.t001", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summarized_characteristics_of_tissue_samples_/1022129", "title"=>"Summarized characteristics of tissue samples.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-05-09 03:12:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1492067"], "description"=>"<p>miRID = miRID from miRBase version 20.</p><p>Log FC =  log fold change.</p><p>Ave. Expr =  average expression.</p><p>Adj. P. Val =  Adjustment of P Value.</p>", "links"=>[], "tags"=>["Computational biology", "genome analysis", "Transcriptome analysis", "Genome expression analysis", "genetics", "Cancer genetics", "genomics", "oncology", "Cancers and neoplasms", "Gynecological tumors", "Ovarian cancer", "Cancer detection and diagnosis", "Cancer risk factors", "biomarkers", "ovarian", "cancer"], "article_id"=>1022130, "categories"=>["Biological Sciences"], "users"=>["Lin Wang", "Miao-Jun Zhu", "Ai-Min Ren", "Hong-Fei Wu", "Wu-Mei Han", "Ruo-Ying Tan", "Rui-Qin Tu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096472.t002", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Selected_list_of_biomarkers_for_ovarian_cancer_diagnosis_/1022130", "title"=>"Selected list of biomarkers for ovarian cancer diagnosis.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-05-09 03:12:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1492068"], "description"=>"<p>miRID = miRID from miRBase version 20.</p><p>Log FC (<b>CE+CB vs. Normal</b>) = log2 fold change for (<b>CE+CB vs. Normal</b>).</p><p>Log FC (<b>CE vs. Normal</b>) = log2 fold change for (<b>CE vs. Normal</b>).</p>", "links"=>[], "tags"=>["Computational biology", "genome analysis", "Transcriptome analysis", "Genome expression analysis", "genetics", "Cancer genetics", "genomics", "oncology", "Cancers and neoplasms", "Gynecological tumors", "Ovarian cancer", "Cancer detection and diagnosis", "Cancer risk factors", "mir-183-96-182", "mir200", "ovarian"], "article_id"=>1022131, "categories"=>["Biological Sciences"], "users"=>["Lin Wang", "Miao-Jun Zhu", "Ai-Min Ren", "Hong-Fei Wu", "Wu-Mei Han", "Ruo-Ying Tan", "Rui-Qin Tu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096472.t003", "stats"=>{"downloads"=>4, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_miRNA_expression_profile_of_miR_183_96_182_cluster_and_miR200_cluster_in_ovarian_cancer_/1022131", "title"=>"miRNA expression profile of miR-183-96-182 cluster and miR200 cluster in ovarian cancer.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-05-09 03:12:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1492074"], "description"=>"<div><p>Epithelial ovarian cancer (EOC) is the most common gynecologic malignancy. To identify the micro-ribonucleic acids (miRNAs) expression profile in EOC tissues that may serve as a novel diagnostic biomarker for EOC detection, the expression of 1722 miRNAs from 15 normal ovarian tissue samples and 48 ovarian cancer samples was profiled by using a quantitative real-time polymerase chain reaction (qRT-PCR) assay. A ten-microRNA signature (hsa-miR-1271-5p, hsa-miR-574-3p, hsa-miR-182-5p, hsa-miR-183-5p, hsa-miR-96-5p, hsa-miR-15b-5p, hsa-miR-182-3p, hsa-miR-141-5p, hsa-miR-130b-5p, and hsa-miR-135b-3p) was identified to be able to distinguish human ovarian cancer tissues from normal tissues with 97% sensitivity and 92% specificity. Two miRNA clusters of miR183-96-183 (miR-96-5p, and miR-182, miR183) and miR200 (miR-141-5p, miR200a, b, c and miR429) are significantly up-regulated in ovarian cancer tissue samples compared to those of normal tissue samples, suggesting theses miRNAs may be involved in ovarian cancer development.</p></div>", "links"=>[], "tags"=>["Computational biology", "genome analysis", "Transcriptome analysis", "Genome expression analysis", "genetics", "Cancer genetics", "genomics", "oncology", "Cancers and neoplasms", "Gynecological tumors", "Ovarian cancer", "Cancer detection and diagnosis", "Cancer risk factors", "ten-microrna", "genome-wide", "microrna", "profiling", "epithelial", "ovarian"], "article_id"=>1022136, "categories"=>["Biological Sciences"], "users"=>["Lin Wang", "Miao-Jun Zhu", "Ai-Min Ren", "Hong-Fei Wu", "Wu-Mei Han", "Ruo-Ying Tan", "Rui-Qin Tu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096472", "stats"=>{"downloads"=>9, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_Ten_MicroRNA_Signature_Identified_from_a_Genome_Wide_MicroRNA_Expression_Profiling_in_Human_Epithelial_Ovarian_Cancer_/1022136", "title"=>"A Ten-MicroRNA Signature Identified from a Genome-Wide MicroRNA Expression Profiling in Human Epithelial Ovarian Cancer", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-05-09 03:12:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1492060"], "description"=>"<p>A) The plot of miRNA assays used to profile compared samples: fold change (y-axis) against normalized Ct measurements. B) Volcano plot of the resulting p-values of the t-test (y-axis) between the C and N groups. 305 miRNAs show FDR-adjusted p-values below 0.1 and fold change above 2 (shown in red). C) Hierarchical clustering (R package pvclust) of the 45 ovarian cancer tissues and 14 ovarian normal tissues based on top 50 most variable miRNA assays. For each cluster in hierarchical clustering, quantities called <i>p</i>-values (approximately unbiased <i>p</i>-value (red) and Bootstrap Probability p-value (green)) are calculated via multi-scale bootstrap resampling. <i>P</i>-value of a cluster is a value between 0 and 1, which indicates how strong the cluster is supported by data. D) 17% of the variance observed in the Ct measurements of top 50 most variable miRNA assays across all samples can be explained by sample pathology status (C or N). The remaining covariates considered here (source = hospital source, survival, tumor histology, FIGO stage, tumor grade, relapse, and stage) explain 24% of the variance.</p>", "links"=>[], "tags"=>["Computational biology", "genome analysis", "Transcriptome analysis", "Genome expression analysis", "genetics", "Cancer genetics", "genomics", "oncology", "Cancers and neoplasms", "Gynecological tumors", "Ovarian cancer", "Cancer detection and diagnosis", "Cancer risk factors", "45", "ovarian", "cancer", "epithelial", "carcinoma", "borderline", "14"], "article_id"=>1022123, "categories"=>["Biological Sciences"], "users"=>["Lin Wang", "Miao-Jun Zhu", "Ai-Min Ren", "Hong-Fei Wu", "Wu-Mei Han", "Ruo-Ying Tan", "Rui-Qin Tu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096472.g001", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_between_45_ovarian_cancer_39_epithelial_carcinoma_and_6_borderline_tissues_and_14_normal_ovarian_tissues_/1022123", "title"=>"Comparison between 45 ovarian cancer (39 epithelial carcinoma and 6 borderline tissues) and 14 normal ovarian tissues.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-09 03:12:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1492062"], "description"=>"<p>A) Error rate produced by different classification algorithms as a function of the number of prediction markers used. Leave-one-out cross-validation procedure was used to estimate resulting error rates. B) Percent overlapping of predictor miRNA selected from the different training sets of samples used. C) Leave-one-out cross validation results: each sample class probability (y-axis) is estimated based on SVM model learned from all other samples. Tissues (cancer black, normal red) are represented by classification probability of being cancer. D) ROC curve based on leave-one-out cross validation results using SVM method.</p>", "links"=>[], "tags"=>["Computational biology", "genome analysis", "Transcriptome analysis", "Genome expression analysis", "genetics", "Cancer genetics", "genomics", "oncology", "Cancers and neoplasms", "Gynecological tumors", "Ovarian cancer", "Cancer detection and diagnosis", "Cancer risk factors", "rates", "leave-one-out", "validation", "markers", "mirna"], "article_id"=>1022125, "categories"=>["Biological Sciences"], "users"=>["Lin Wang", "Miao-Jun Zhu", "Ai-Min Ren", "Hong-Fei Wu", "Wu-Mei Han", "Ruo-Ying Tan", "Rui-Qin Tu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096472.g002", "stats"=>{"downloads"=>1, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Determination_of_error_rates_by_leave_one_out_cross_validation_vs_number_of_markers_and_miRNA_markers_overlapping_/1022125", "title"=>"Determination of error rates by leave-one-out cross validation vs. number of markers and miRNA markers overlapping.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-09 03:12:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/1492065"], "description"=>"<p>A) Prediction probabilities (ovarian cancer) for each sample used in this study (C = Cancer; N = Normal). B) ROC curve. C) Prediction error across different tissue groups: normal tissue (N), epithelial carcinomas tissues (CE) and borderline tissues (CB). D) Prediction error within tumor grade groups [Increased error in lower grade samples (but not significant)].</p>", "links"=>[], "tags"=>["Computational biology", "genome analysis", "Transcriptome analysis", "Genome expression analysis", "genetics", "Cancer genetics", "genomics", "oncology", "Cancers and neoplasms", "Gynecological tumors", "Ovarian cancer", "Cancer detection and diagnosis", "Cancer risk factors", "cancer", "classification", "10", "mirnas", "svm", "algorithm", "leave-one-out"], "article_id"=>1022127, "categories"=>["Biological Sciences"], "users"=>["Lin Wang", "Miao-Jun Zhu", "Ai-Min Ren", "Hong-Fei Wu", "Wu-Mei Han", "Ruo-Ying Tan", "Rui-Qin Tu"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0096472.g003", "stats"=>{"downloads"=>2, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Ovarian_cancer_classification_performance_for_the_10_selected_miRNAs_Table_2_using_SVM_algorithm_and_leave_one_out_cross_validation_/1022127", "title"=>"Ovarian cancer classification performance for the 10 selected miRNAs (<b>Table 2</b>) using SVM algorithm and leave-one-out cross-validation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-05-09 03:12:10"}

PMC Usage Stats | Further Information

  • {"unique-ip"=>"39", "full-text"=>"35", "pdf"=>"22", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"8", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2014", "month"=>"5"}
  • {"unique-ip"=>"46", "full-text"=>"39", "pdf"=>"23", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"14", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"6"}
  • {"unique-ip"=>"18", "full-text"=>"18", "pdf"=>"13", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"4"}
  • {"unique-ip"=>"21", "full-text"=>"19", "pdf"=>"9", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"8", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"5"}
  • {"unique-ip"=>"19", "full-text"=>"19", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"6", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2015", "month"=>"6"}
  • {"unique-ip"=>"30", "full-text"=>"35", "pdf"=>"18", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"11", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2015", "month"=>"7"}
  • {"unique-ip"=>"26", "full-text"=>"29", "pdf"=>"17", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2015", "month"=>"3"}
  • {"unique-ip"=>"25", "full-text"=>"34", "pdf"=>"15", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2015", "month"=>"2"}
  • {"unique-ip"=>"25", "full-text"=>"18", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"10", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"8"}
  • {"unique-ip"=>"28", "full-text"=>"22", "pdf"=>"17", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"9"}
  • {"unique-ip"=>"26", "full-text"=>"21", "pdf"=>"12", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2015", "month"=>"10"}
  • {"unique-ip"=>"34", "full-text"=>"35", "pdf"=>"18", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"7"}
  • {"unique-ip"=>"35", "full-text"=>"31", "pdf"=>"21", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"6", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"8"}
  • {"unique-ip"=>"49", "full-text"=>"30", "pdf"=>"10", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"36", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"9"}
  • {"unique-ip"=>"10", "full-text"=>"9", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"7", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"1"}
  • {"unique-ip"=>"37", "full-text"=>"31", "pdf"=>"14", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"12", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2014", "month"=>"10"}
  • {"unique-ip"=>"15", "full-text"=>"13", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2016", "month"=>"2"}
  • {"unique-ip"=>"26", "full-text"=>"28", "pdf"=>"10", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"7", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2014", "month"=>"11"}
  • {"unique-ip"=>"28", "full-text"=>"29", "pdf"=>"20", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"12"}
  • {"unique-ip"=>"26", "full-text"=>"28", "pdf"=>"11", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2015", "month"=>"1"}
  • {"unique-ip"=>"32", "full-text"=>"23", "pdf"=>"20", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2015", "month"=>"11"}
  • {"unique-ip"=>"15", "full-text"=>"12", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"12"}
  • {"unique-ip"=>"23", "full-text"=>"26", "pdf"=>"16", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"3"}
  • {"unique-ip"=>"23", "full-text"=>"21", "pdf"=>"12", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"6", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2016", "month"=>"4"}
  • {"unique-ip"=>"17", "full-text"=>"14", "pdf"=>"13", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2016", "month"=>"5"}
  • {"unique-ip"=>"17", "full-text"=>"16", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"6", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"6"}
  • {"unique-ip"=>"13", "full-text"=>"11", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"6", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"7"}
  • {"unique-ip"=>"12", "full-text"=>"11", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"8"}
  • {"unique-ip"=>"10", "full-text"=>"10", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"9"}
  • {"unique-ip"=>"14", "full-text"=>"20", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
  • {"unique-ip"=>"16", "full-text"=>"16", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2016", "month"=>"11"}
  • {"unique-ip"=>"22", "full-text"=>"24", "pdf"=>"12", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"10", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2016", "month"=>"12"}
  • {"unique-ip"=>"26", "full-text"=>"25", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"1"}
  • {"unique-ip"=>"13", "full-text"=>"19", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"2"}
  • {"unique-ip"=>"21", "full-text"=>"24", "pdf"=>"9", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"3"}
  • {"unique-ip"=>"15", "full-text"=>"15", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"4"}
  • {"unique-ip"=>"28", "full-text"=>"23", "pdf"=>"11", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2017", "month"=>"5"}
  • {"unique-ip"=>"12", "full-text"=>"14", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2017", "month"=>"6"}
  • {"unique-ip"=>"10", "full-text"=>"7", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"7"}
  • {"unique-ip"=>"23", "full-text"=>"20", "pdf"=>"18", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2017", "month"=>"8"}
  • {"unique-ip"=>"21", "full-text"=>"21", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"6", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2017", "month"=>"9"}
  • {"unique-ip"=>"12", "full-text"=>"11", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"10"}
  • {"unique-ip"=>"18", "full-text"=>"23", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"10", "cited-by"=>"0", "year"=>"2017", "month"=>"11"}
  • {"unique-ip"=>"14", "full-text"=>"13", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"12"}
  • {"unique-ip"=>"16", "full-text"=>"17", "pdf"=>"9", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2018", "month"=>"1"}
  • {"unique-ip"=>"17", "full-text"=>"20", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
  • {"unique-ip"=>"15", "full-text"=>"14", "pdf"=>"8", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"10", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"1"}
  • {"unique-ip"=>"14", "full-text"=>"16", "pdf"=>"7", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
  • {"unique-ip"=>"29", "full-text"=>"38", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"31", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
  • {"unique-ip"=>"13", "full-text"=>"13", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
  • {"unique-ip"=>"17", "full-text"=>"18", "pdf"=>"7", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"15", "full-text"=>"13", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"15", "full-text"=>"16", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"15", "full-text"=>"15", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"8", "full-text"=>"11", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"9", "full-text"=>"13", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"14", "full-text"=>"15", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"14", "full-text"=>"15", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"16", "full-text"=>"14", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"9", "full-text"=>"9", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"9", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}
  • {"unique-ip"=>"9", "full-text"=>"9", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}
  • {"unique-ip"=>"14", "full-text"=>"11", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"10"}

Relative Metric

{"start_date"=>"2014-01-01T00:00:00Z", "end_date"=>"2014-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences/Biochemistry", "average_usage"=>[282]}, {"subject_area"=>"/Medicine and health sciences/Anatomy", "average_usage"=>[266]}, {"subject_area"=>"/Medicine and health sciences/Diagnostic medicine", "average_usage"=>[257]}]}
Loading … Spinner
There are currently no alerts