MORPHEUS, a Webtool for Transcription Factor Binding Analysis Using Position Weight Matrices with Dependency
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{"title"=>"MORPHEUS, a webtool for transcription factor binding analysis using position weight matrices with dependency", "type"=>"journal", "authors"=>[{"first_name"=>"Eugenio Gómez", "last_name"=>"Minguet", "scopus_author_id"=>"6505637288"}, {"first_name"=>"Stéphane", "last_name"=>"Segard", "scopus_author_id"=>"55236998000"}, {"first_name"=>"Céline", "last_name"=>"Charavay", "scopus_author_id"=>"6506579089"}, {"first_name"=>"François", "last_name"=>"Parcy", "scopus_author_id"=>"6603627872"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84942791752", "sgr"=>"84942791752", "doi"=>"10.1371/journal.pone.0135586", "pui"=>"606153892", "pmid"=>"26285209", "issn"=>"19326203"}, "id"=>"a4f1a65a-27f4-3427-9747-c185ce9d3ed4", "abstract"=>"Transcriptional networks are central to any biological process and changes affecting transcription factors or their binding sites in the genome are a key factor driving evolution. As more organisms are being sequenced, tools are needed to easily predict transcription factor binding sites (TFBS) presence and affinity from mere inspection of genomic sequences. Although many TFBS discovery algorithms exist, tools for using the DNA binding models they generate are relatively scarce and their use is limited among the biologist community by the lack of flexible and user-friendly tools. We have developed a suite of web tools (called Morpheus) based on the proven Position Weight Matrices (PWM) formalism that can be used without any programing skills and incorporates some unique features such as the presence of dependencies between nucleotides positions or the possibility to compute the predicted occupancy of a large regulatory region using a biophysical model. To illustrate the possibilities and simplicity of Morpheus tools in functional and evolutionary analysis, we have analysed the regulatory link between LEAFY, a key plant transcription factor involved in flower development, and its direct target gene APETALA1 during the divergence of Brassicales clade.", "link"=>"http://www.mendeley.com/research/morpheus-webtool-transcription-factor-binding-analysis-using-position-weight-matrices-dependency", "reader_count"=>19, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Researcher"=>7, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>4, "Student > Postgraduate"=>1, "Student > Master"=>3, "Other"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Researcher"=>7, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>4, "Student > Postgraduate"=>1, "Student > Master"=>3, "Other"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Biochemistry, Genetics and Molecular Biology"=>1, "Agricultural and Biological Sciences"=>14, "Veterinary Science and Veterinary Medicine"=>1, "Chemistry"=>1}, "reader_count_by_subdiscipline"=>{"Chemistry"=>{"Chemistry"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>14}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Unspecified"=>{"Unspecified"=>2}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Chile"=>1, "France"=>1}, "group_count"=>0}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2215798", "https://ndownloader.figshare.com/files/2215799", "https://ndownloader.figshare.com/files/2215800", "https://ndownloader.figshare.com/files/2215801", "https://ndownloader.figshare.com/files/2215802"], "description"=>"<div><p>Transcriptional networks are central to any biological process and changes affecting transcription factors or their binding sites in the genome are a key factor driving evolution. As more organisms are being sequenced, tools are needed to easily predict transcription factor binding sites (TFBS) presence and affinity from mere inspection of genomic sequences. Although many TFBS discovery algorithms exist, tools for using the DNA binding models they generate are relatively scarce and their use is limited among the biologist community by the lack of flexible and user-friendly tools. We have developed a suite of web tools (called Morpheus) based on the proven Position Weight Matrices (PWM) formalism that can be used without any programing skills and incorporates some unique features such as the presence of dependencies between nucleotides positions or the possibility to compute the predicted occupancy of a large regulatory region using a biophysical model. To illustrate the possibilities and simplicity of Morpheus tools in functional and evolutionary analysis, we have analysed the regulatory link between LEAFY, a key plant transcription factor involved in flower development, and its direct target gene <i>APETALA1</i> during the divergence of Brassicales clade.</p></div>", "links"=>[], "tags"=>["target gene APETALA 1", "biologist community", "presence", "Brassicales clade", "binding sites", "TFBS discovery algorithms", "transcription factor binding sites", "Transcription Factor Binding Analysis", "programing skills", "flower development", "plant transcription factor", "leafy", "transcription factors", "DNA binding models", "MORPHEUS", "Dependency Transcriptional networks", "nucleotides positions", "position weight matrices", "Morpheus tools", "genomic sequences", "web tools", "pwm"], "article_id"=>1513418, "categories"=>["Biological Sciences"], "users"=>["Eugenio Gómez Minguet", "Stéphane Segard", "Céline Charavay", "François Parcy"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0135586.s001", "https://dx.doi.org/10.1371/journal.pone.0135586.s002", "https://dx.doi.org/10.1371/journal.pone.0135586.s003", "https://dx.doi.org/10.1371/journal.pone.0135586.s004", "https://dx.doi.org/10.1371/journal.pone.0135586.s005"], "stats"=>{"downloads"=>11, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MORPHEUS_a_Webtool_for_Transcription_Factor_Binding_Analysis_Using_Position_Weight_Matrices_with_Dependency_/1513418", "title"=>"MORPHEUS, a Webtool for Transcription Factor Binding Analysis Using Position Weight Matrices with Dependency", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2015-08-18 03:35:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/2215791"], "description"=>"<p>The Morpheus ‘ROC’ tools computes the ROC-AUC value as a measure of the model predictive power. <b>A)</b> The histogram graphical output displays the distribution of score values for the best binding sites present on each DNA sequence. <b>B)</b> ROC data output for three binding models: two consensus motifs and LFY-trip (input data has been generated using the Morpheus ‘Occupancy’ tool). The LFY-trip model largely outperforms the two consensus models.</p>", "links"=>[], "tags"=>["target gene APETALA 1", "biologist community", "presence", "Brassicales clade", "binding sites", "TFBS discovery algorithms", "transcription factor binding sites", "Transcription Factor Binding Analysis", "programing skills", "flower development", "plant transcription factor", "leafy", "transcription factors", "DNA binding models", "MORPHEUS", "Dependency Transcriptional networks", "nucleotides positions", "position weight matrices", "Morpheus tools", "genomic sequences", "web tools", "pwm"], "article_id"=>1513411, "categories"=>["Biological Sciences"], "users"=>["Eugenio Gómez Minguet", "Stéphane Segard", "Céline Charavay", "François Parcy"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0135586.g002", "stats"=>{"downloads"=>2, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_performance_of_a_TF_model_can_be_evaluated_by_its_capability_to_discriminate_between_bound_and_non_bound_regions_as_determined_from_a_ChIP_Seq_experiment_/1513411", "title"=>"The performance of a TF model can be evaluated by its capability to discriminate between bound and non-bound regions as determined from a ChIP-Seq experiment.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-08-18 03:35:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/2215790"], "description"=>"<p>The tool Score scans DNA regions and computes the scores of TFBS. The bottom left graph shows TFBS locations and scores; such score profile is generated for each sequence submitted. The Occupancy tool computes the TF predicted occupancy of each DNA region taking as input sequence files (in fasta format) and a binding model information (<i>m</i>PWM format). Complete results are written in text files and also displayed as graphical outputs for quick results overview. Bottom right panel shows a occupancy comparison between different DNA regions. The bottom central panel illustrates the ROC-AUC curve and value obtained with the ROC-AUC tool.</p>", "links"=>[], "tags"=>["target gene APETALA 1", "biologist community", "presence", "Brassicales clade", "binding sites", "TFBS discovery algorithms", "transcription factor binding sites", "Transcription Factor Binding Analysis", "programing skills", "flower development", "plant transcription factor", "leafy", "transcription factors", "DNA binding models", "MORPHEUS", "Dependency Transcriptional networks", "nucleotides positions", "position weight matrices", "Morpheus tools", "genomic sequences", "web tools", "pwm"], "article_id"=>1513410, "categories"=>["Biological Sciences"], "users"=>["Eugenio Gómez Minguet", "Stéphane Segard", "Céline Charavay", "François Parcy"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0135586.g001", "stats"=>{"downloads"=>3, "page_views"=>33, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Morpheus_flowchart_and_example_of_result_representation_/1513410", "title"=>"Morpheus flowchart and example of result representation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-08-18 03:35:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/2215794"], "description"=>"<p>Genomic sequences were obtained from the Phytozome database and 2 kb promoter upstream the ATG were used. Only well annotated genes were used. <b>A)</b> Predicted occupancy (Option limit = -23) for each promoter. Phylogenetic relationships between species are represented. <b>B)</b> Score profile (limit = -23) of some representative promoters. The higher occupancy for <i>AP1</i> promoters in Brassicales (red) suggests that the regulatory link between LFY and <i>AP1</i> in <i>A</i>. <i>thaliana</i> arose before the divergence of this clade. Interestingly, <i>C</i>. <i>papaya</i> with low occupancy in <i>AP1</i> promoter has a candidate BS of very good score downstream the start codon likely to be responsible for a regulation by LFY. In Fabids, the low occupancy values suggest that LFY does not regulate <i>AP1</i>, though some promoters have intermediate occupancy values (green) what will need further analysis.</p>", "links"=>[], "tags"=>["target gene APETALA 1", "biologist community", "presence", "Brassicales clade", "binding sites", "TFBS discovery algorithms", "transcription factor binding sites", "Transcription Factor Binding Analysis", "programing skills", "flower development", "plant transcription factor", "leafy", "transcription factors", "DNA binding models", "MORPHEUS", "Dependency Transcriptional networks", "nucleotides positions", "position weight matrices", "Morpheus tools", "genomic sequences", "web tools", "pwm"], "article_id"=>1513414, "categories"=>["Biological Sciences"], "users"=>["Eugenio Gómez Minguet", "Stéphane Segard", "Céline Charavay", "François Parcy"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0135586.g004", "stats"=>{"downloads"=>0, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolutionary_analysis_of_LFY_binding_on_AP1_promoters_/1513414", "title"=>"Evolutionary analysis of LFY binding on <i>AP1</i> promoters.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-08-18 03:35:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/2215793"], "description"=>"<p><b>A)</b> Score profile graphic output of the Morpheus ‘Score’ tool (option limit = -25) using 2.2 kb upstream of <i>AP1</i> start codon. Red dotted lines show the different promoter sizes and arrows mark the mutated BS, accordingly with promoters set described in [<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135586#pone.0135586.ref039\" target=\"_blank\">39</a>]. <b>B)</b> Predicted occupancy (option All) shows a good correspondence with relative expression of each promoter version as determined experimentally in a published study and summarized: expression levels: +++ (high), ++ (medium), + (low),—(not detectable). The number indicates the size of the promoter (2.2, 1.7, 0.9 or 0.6 kb), m2 and m3 indicate mutations in bs2 and bs3 respectively, ∆1 indicates a deletion of bs1. <i>In vivo</i>, mutations of bs2 and bs3 (promoter 0.6 mutbs2bs3) has only a weak effect while elimination of bs1 drastically affects <i>AP1</i> expression.</p>", "links"=>[], "tags"=>["target gene APETALA 1", "biologist community", "presence", "Brassicales clade", "binding sites", "TFBS discovery algorithms", "transcription factor binding sites", "Transcription Factor Binding Analysis", "programing skills", "flower development", "plant transcription factor", "leafy", "transcription factors", "DNA binding models", "MORPHEUS", "Dependency Transcriptional networks", "nucleotides positions", "position weight matrices", "Morpheus tools", "genomic sequences", "web tools", "pwm"], "article_id"=>1513413, "categories"=>["Biological Sciences"], "users"=>["Eugenio Gómez Minguet", "Stéphane Segard", "Céline Charavay", "François Parcy"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0135586.g003", "stats"=>{"downloads"=>1, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_LEAFY_binding_analysis_in_A_thaliana_AP1_promoter_using_the_Morpheus_suite_with_in_vivo_promoter_expression_study_39_/1513413", "title"=>"Comparison of LEAFY binding analysis in <i>A</i>. <i>thaliana AP1</i> promoter using the Morpheus suite with <i>in vivo</i> promoter expression study [39].", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-08-18 03:35:19"}

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Relative Metric

{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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