Quantification of miRNA-mRNA Interactions
Publication Date
February 14, 2012
Journal
PLOS ONE
Authors
Ander Muniategui, Rubén Nogales Cadenas, Miguél Vázquez, Xabier L. Aranguren, et al
Volume
7
Issue
2
Pages
e30766
DOI
http://doi.org/10.1371/journal.pone.0030766
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0030766
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/22348024
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3279346
Europe PMC
http://europepmc.org/abstract/MED/22348024
Web of Science
000302737400005
Scopus
84856857511
Mendeley
http://www.mendeley.com/research/quantification-mirnamrna-interactions
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Mendeley | Further Information

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CrossRef

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/682905"], "description"=>"<p>For each value of the tuning factor and different number of predicted interactions, the figure shows the probability of drawing the predicted number of experimentally-validated targets by using a hypergeometric test. The figure shows TaLasso enrichment results for different <i>κ<sup>G</sup></i> values (in blue), compared to the enrichment values of GenMiR++ (black crosses) and Pearson Correlation (black dashed).</p>", "links"=>[], "tags"=>["experimentally-validated", "targets", "lds"], "article_id"=>353388, "categories"=>["Biochemistry", "Molecular Biology", "Biological Sciences", "Information And Computing Sciences", "Biophysics"], "users"=>["Ander Muniategui", "Rubén Nogales-Cadenas", "Miguel Vazquez", "Xabier L. Aranguren", "Xabier Agirre", "Aernout Luttun", "Felipe Prósper", "Alberto Pascual-Montano", "Angel Rubio"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030766.g004", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Enrichment_on_experimentally_validated_targets_for_LDS_dataset_/353388", "title"=>"Enrichment on experimentally-validated targets for LDS dataset.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-14 00:56:28"}
  • {"files"=>["https://ndownloader.figshare.com/files/683227"], "description"=>"<p>The table shows the maximum enrichment values (point of minimum p-value) for the union of TaRBase and miRecords, for MCC dataset. N<sub>E</sub>: is the number of experimentally-validated targets rescued in the point of minimum p-value and N<sub>T</sub>: is the total number of predicted targets in that minimum. N<sub>E</sub><sup>500</sup>: is the amount of experimentally-validated targets in the first 500 predicted interactions.</p>", "links"=>[], "tags"=>["enrichment", "experimentally-validated", "targets", "lds"], "article_id"=>353704, "categories"=>["Biochemistry", "Molecular Biology", "Biological Sciences", "Information And Computing Sciences", "Biophysics"], "users"=>["Ander Muniategui", "Rubén Nogales-Cadenas", "Miguel Vazquez", "Xabier L. Aranguren", "Xabier Agirre", "Aernout Luttun", "Felipe Prósper", "Alberto Pascual-Montano", "Angel Rubio"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030766.t002", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Maximum_enrichment_values_on_experimentally_validated_targets_for_LDS_dataset_/353704", "title"=>"Maximum enrichment values on experimentally-validated targets for LDS dataset.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-14 01:01:44"}
  • {"files"=>["https://ndownloader.figshare.com/files/682771"], "description"=>"<p>For each value of the tuning factor and different number of predicted interactions, the figure shows the probability of drawing the predicted number of experimentally-validated targets by using a hypergeometric test. The figure shows TaLasso enrichment results for different <i>κ<sup>G</sup></i> values (in blue), compared to the enrichment values of GenMiR++ (black crosses) and Pearson Correlation (black dashed).</p>", "links"=>[], "tags"=>["experimentally-validated", "targets", "mcc"], "article_id"=>353254, "categories"=>["Biochemistry", "Molecular Biology", "Biological Sciences", "Information And Computing Sciences", "Biophysics"], "users"=>["Ander Muniategui", "Rubén Nogales-Cadenas", "Miguel Vazquez", "Xabier L. Aranguren", "Xabier Agirre", "Aernout Luttun", "Felipe Prósper", "Alberto Pascual-Montano", "Angel Rubio"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030766.g003", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Enrichment_on_experimentally_validated_targets_for_MCC_dataset_/353254", "title"=>"Enrichment on experimentally-validated targets for MCC dataset.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-14 00:54:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/348019", "https://ndownloader.figshare.com/files/348054", "https://ndownloader.figshare.com/files/348088", "https://ndownloader.figshare.com/files/348209", "https://ndownloader.figshare.com/files/348276", "https://ndownloader.figshare.com/files/348325", "https://ndownloader.figshare.com/files/348370", "https://ndownloader.figshare.com/files/348491"], "description"=>"<div><p>miRNAs are small RNA molecules (<em>′</em> 22<em>nt</em>) that interact with their corresponding target mRNAs inhibiting the translation of the mRNA into proteins and cleaving the target mRNA. This second effect diminishes the overall expression of the target mRNA. Several miRNA-mRNA relationship databases have been deployed, most of them based on sequence complementarities. However, the number of false positives in these databases is large and they do not overlap completely. Recently, it has been proposed to combine expression measurement from both miRNA and mRNA and sequence based predictions to achieve more accurate relationships. In our work, we use LASSO regression with non-positive constraints to integrate both sources of information. LASSO enforces the sparseness of the solution and the non-positive constraints restrict the search of miRNA targets to those with down-regulation effects on the mRNA expression. We named this method TaLasso (miRNA-Target LASSO).</p> <p>We used TaLasso on two public datasets that have paired expression levels of human miRNAs and mRNAs. The top ranked interactions recovered by TaLasso are especially enriched (more than using any other algorithm) in experimentally validated targets. The functions of the genes with mRNA transcripts in the top-ranked interactions are meaningful. This is not the case using other algorithms.</p> <p>TaLasso is available as Matlab or R code. There is also a web-based tool for human miRNAs at <a href=\"http://talasso.cnb.csic.es/\">http://talasso.cnb.csic.es/</a>.</p> </div>", "links"=>[], "tags"=>["quantification", "mirna-mrna", "interactions"], "article_id"=>128817, "categories"=>["Biochemistry", "Molecular Biology", "Biological Sciences", "Information And Computing Sciences", "Biophysics"], "users"=>["Ander Muniategui", "Rubén Nogales-Cadenas", "Miguel Vazquez", "Xabier L. Aranguren", "Xabier Agirre", "Aernout Luttun", "Felipe Prósper", "Alberto Pascual-Montano", "Angel Rubio"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0030766.s001", "https://dx.doi.org/10.1371/journal.pone.0030766.s002", "https://dx.doi.org/10.1371/journal.pone.0030766.s003", "https://dx.doi.org/10.1371/journal.pone.0030766.s004", "https://dx.doi.org/10.1371/journal.pone.0030766.s005", "https://dx.doi.org/10.1371/journal.pone.0030766.s006", "https://dx.doi.org/10.1371/journal.pone.0030766.s007", "https://dx.doi.org/10.1371/journal.pone.0030766.s008"], "stats"=>{"downloads"=>46, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Quantification_of_miRNA_mRNA_Interactions/128817", "title"=>"Quantification of miRNA-mRNA Interactions", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-02-14 02:26:57"}
  • {"files"=>["https://ndownloader.figshare.com/files/683035"], "description"=>"<p>Enrichment analysis on KEGG pathways of the 200 top-ranked genes. The figure shows the results for TaLasso, GenMiR++ and Pearson Correlation. In the figure, the x-axis indicates the number of mRNAs on each enriched pathway. The associated p-value is also shown. The list of genes on each enriched KEGG pathway is included in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0030766#pone.0030766.s004\" target=\"_blank\">text S2</a>.</p>", "links"=>[], "tags"=>["pathway", "enrichment", "lds"], "article_id"=>353519, "categories"=>["Biochemistry", "Molecular Biology", "Biological Sciences", "Information And Computing Sciences", "Biophysics"], "users"=>["Ander Muniategui", "Rubén Nogales-Cadenas", "Miguel Vazquez", "Xabier L. Aranguren", "Xabier Agirre", "Aernout Luttun", "Felipe Prósper", "Alberto Pascual-Montano", "Angel Rubio"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030766.g005", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_KEGG_pathway_enrichment_results_for_LDS_dataset_/353519", "title"=>"KEGG pathway enrichment results for LDS dataset.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-14 00:58:39"}
  • {"files"=>["https://ndownloader.figshare.com/files/683189"], "description"=>"<p>The table shows the maximum enrichment values (point of minimum p-value) for the union of TaRBase and miRecords, for MCC dataset. N<sub>E</sub>: is the number of experimentally-validated targets rescued in the point of minimum p-value and N<sub>T</sub>: is the total number of predicted targets in that minimum. N<sub>E</sub><sup>500</sup>: is the amount of experimentally-validated targets in the first 500 predicted interactions.</p>", "links"=>[], "tags"=>["enrichment", "experimentally-validated", "targets", "mcc"], "article_id"=>353660, "categories"=>["Biochemistry", "Molecular Biology", "Biological Sciences", "Information And Computing Sciences", "Biophysics"], "users"=>["Ander Muniategui", "Rubén Nogales-Cadenas", "Miguel Vazquez", "Xabier L. Aranguren", "Xabier Agirre", "Aernout Luttun", "Felipe Prósper", "Alberto Pascual-Montano", "Angel Rubio"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030766.t001", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Maximum_enrichment_values_on_experimentally_validated_targets_for_MCC_dataset_/353660", "title"=>"Maximum enrichment values on experimentally-validated targets for MCC dataset.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-14 01:01:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/683267"], "description"=>"<p>OV: Ovarian Cancer, BlC: Bladder Cancer; EC: Esophageal Cancer; CC: Colon/Colorectal Cancer; LC: Lung Cancer; BrC: Breast Cancer, NC: Nasopharingeal Cancer, PC: Prostate Cancer; GC: Gastric Cancer.</p><p>The experimentally-validated targets included in the top 500 targets predicted were selected and their literature references included on TaRBase, miRecords and miRWalk were analyzed in search of biological relevancy. In the table only those interactions with a literature reference related with MCC environment have been included. This was made for the predictions of TaLasso, GenMiR++ and Pearson Correlation.</p>", "links"=>[], "tags"=>["experimentally-validated", "targets", "cancer", "been", "mcc"], "article_id"=>353746, "categories"=>["Biochemistry", "Molecular Biology", "Biological Sciences", "Information And Computing Sciences", "Biophysics"], "users"=>["Ander Muniategui", "Rubén Nogales-Cadenas", "Miguel Vazquez", "Xabier L. Aranguren", "Xabier Agirre", "Aernout Luttun", "Felipe Prósper", "Alberto Pascual-Montano", "Angel Rubio"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030766.t003", "stats"=>{"downloads"=>3, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicted_experimentally_validated_targets_and_the_cancer_to_which_they_have_been_related_in_the_literature_results_for_MCC_dataset_/353746", "title"=>"Predicted experimentally-validated targets and the cancer to which they have been related in the literature: results for MCC dataset.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-14 01:02:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/683141"], "description"=>"<p>CLL: Chronic Lymphoblastic Leukaemia, ALL: Acute Lymphoblastic Leukaemia, AML: Acute Myeloid Leukaemia, IC: Immunce Cells, IR: Immune Response, HSC: Haematopoietic SC.</p><p>The experimentally-validated targets included in the top 500 targets predicted were selected and their literature references included on TaRBase, miRecords and miRWalk were analyzed in search of biological relevancy. In the table only those interactions with a literature reference related with LDS environment have been included. This was made for the predictions of TaLasso, GenMiR++ and Pearson Correlation.</p>", "links"=>[], "tags"=>["experimentally-validated", "targets", "cancer", "been", "lds"], "article_id"=>353622, "categories"=>["Biochemistry", "Molecular Biology", "Biological Sciences", "Information And Computing Sciences", "Biophysics"], "users"=>["Ander Muniategui", "Rubén Nogales-Cadenas", "Miguel Vazquez", "Xabier L. Aranguren", "Xabier Agirre", "Aernout Luttun", "Felipe Prósper", "Alberto Pascual-Montano", "Angel Rubio"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030766.t004", "stats"=>{"downloads"=>4, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicted_experimentally_validated_targets_and_the_cancer_to_which_they_have_been_related_in_the_literature_results_for_LDS_dataset_/353622", "title"=>"Predicted experimentally-validated targets and the cancer to which they have been related in the literature: results for LDS dataset.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-14 01:00:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/682656"], "description"=>"<p>In the figure the LOOCV mean squared errors for different κ values of the <i>global tuning parameter</i> for MCC and LDS datasets are shown.</p>", "links"=>[], "tags"=>["errors", "validation", "tuning"], "article_id"=>353139, "categories"=>["Biochemistry", "Molecular Biology", "Biological Sciences", "Information And Computing Sciences", "Biophysics"], "users"=>["Ander Muniategui", "Rubén Nogales-Cadenas", "Miguel Vazquez", "Xabier L. Aranguren", "Xabier Agirre", "Aernout Luttun", "Felipe Prósper", "Alberto Pascual-Montano", "Angel Rubio"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030766.g002", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MSE_errors_for_Cross_Validation_analysis_for_global_tuning_parameters_/353139", "title"=>"MSE errors for Cross Validation analysis for <i>global tuning parameters</i>.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-14 00:52:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/682545"], "description"=>"<p>The overlap among the different databases is small. With reference to databases with experimentally-validated targets, the union of miRecords and TarBase includes 623 interactions that are also cited in any of the computationally predicted databases. This number rises to 4372 in case miRWalk is also considered.</p>", "links"=>[], "tags"=>["interactions", "databases", "mirna", "targets", "been", "putative"], "article_id"=>353010, "categories"=>["Biochemistry", "Molecular Biology", "Biological Sciences", "Information And Computing Sciences", "Biophysics"], "users"=>["Ander Muniategui", "Rubén Nogales-Cadenas", "Miguel Vazquez", "Xabier L. Aranguren", "Xabier Agirre", "Aernout Luttun", "Felipe Prósper", "Alberto Pascual-Montano", "Angel Rubio"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0030766.g001", "stats"=>{"downloads"=>5, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Shared_interactions_among_the_different_databases_of_human_miRNA_targets_that_have_been_used_as_initial_set_of_putative_interactions_/353010", "title"=>"Shared interactions among the different databases of human miRNA targets that have been used as initial set of putative interactions.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-14 00:50:10"}

PMC Usage Stats | Further Information

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Relative Metric

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