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{"title"=>"Gene network landscape of the ciliate tetrahymena thermophila", "type"=>"journal", "authors"=>[{"first_name"=>"Jie", "last_name"=>"Xiong", "scopus_author_id"=>"25926224800"}, {"first_name"=>"Dongxia", "last_name"=>"Yuan", "scopus_author_id"=>"36560693500"}, {"first_name"=>"Jeffrey S.", "last_name"=>"Fillingham", "scopus_author_id"=>"6602448383"}, {"first_name"=>"Jyoti", "last_name"=>"Garg", "scopus_author_id"=>"21734283600"}, {"first_name"=>"Xingyi", "last_name"=>"Lu", "scopus_author_id"=>"41561838500"}, {"first_name"=>"Yue", "last_name"=>"Chang", "scopus_author_id"=>"7501844158"}, {"first_name"=>"Yifan", "last_name"=>"Liu", "scopus_author_id"=>"36826419400"}, {"first_name"=>"Chengjie", "last_name"=>"Fu", "scopus_author_id"=>"8395868300"}, {"first_name"=>"Ronald E.", "last_name"=>"Pearlman", "scopus_author_id"=>"7102886305"}, {"first_name"=>"Wei", "last_name"=>"Miao", "scopus_author_id"=>"9039929300"}], "year"=>2011, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"361828949", "issn"=>"19326203", "doi"=>"10.1371/journal.pone.0020124", "scopus"=>"2-s2.0-79957560183", "pmid"=>"21637855", "sgr"=>"79957560183"}, "id"=>"78954308-f557-3cb8-849a-0342dd4110af", "abstract"=>"BACKGROUND: Genome-wide expression data of gene microarrays can be used to infer gene networks. At a cellular level, a gene network provides a picture of the modules in which genes are densely connected, and of the hub genes, which are highly connected with other genes. A gene network is useful to identify the genes involved in the same pathway, in a protein complex or that are co-regulated. In this study, we used different methods to find gene networks in the ciliate Tetrahymena thermophila, and describe some important properties of this network, such as modules and hubs.\\n\\nMETHODOLOGY/PRINCIPAL FINDINGS: Using 67 single channel microarrays, we constructed the Tetrahymena gene network (TGN) using three methods: the Pearson correlation coefficient (PCC), the Spearman correlation coefficient (SCC) and the context likelihood of relatedness (CLR) algorithm. The accuracy and coverage of the three networks were evaluated using four conserved protein complexes in yeast. The CLR network with a Z-score threshold 3.49 was determined to be the most robust. The TGN was partitioned, and 55 modules were found. In addition, analysis of the arbitrarily determined 1200 hubs showed that these hubs could be sorted into six groups according to their expression profiles. We also investigated human disease orthologs in Tetrahymena that are missing in yeast and provide evidence indicating that some of these are involved in the same process in Tetrahymena as in human.\\n\\nCONCLUSIONS/SIGNIFICANCE: This study constructed a Tetrahymena gene network, provided new insights to the properties of this biological network, and presents an important resource to study Tetrahymena genes at the pathway level.", "link"=>"http://www.mendeley.com/research/gene-network-landscape-ciliate-tetrahymena-thermophila", "reader_count"=>33, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Researcher"=>6, "Student > Ph. D. Student"=>9, "Student > Postgraduate"=>3, "Student > Master"=>6, "Other"=>1, "Student > Bachelor"=>5, "Lecturer"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Researcher"=>6, "Student > Ph. D. Student"=>9, "Student > Postgraduate"=>3, "Student > Master"=>6, "Other"=>1, "Student > Bachelor"=>5, "Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Biochemistry, Genetics and Molecular Biology"=>5, "Agricultural and Biological Sciences"=>24, "Computer Science"=>2}, "reader_count_by_subdiscipline"=>{"Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>24}, "Computer Science"=>{"Computer Science"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>5}, "Unspecified"=>{"Unspecified"=>2}}, "reader_count_by_country"=>{"Greece"=>1, "United States"=>1}, "group_count"=>0}

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• http://doi.org/10.1371/journal.pone.0065683
• http://doi.org/10.1007/s11427-011-4194-6
• http://doi.org/10.1002/clen.201300351
• http://doi.org/10.1371/journal.pone.0078848
• http://doi.org/10.1016/j.softx.2017.06.006
• http://doi.org/10.1016/j.cub.2018.01.047
• http://doi.org/10.1074/mcp.M112.026575
• http://doi.org/10.1016/j.jprot.2013.09.018
• http://doi.org/10.1091/mbc.e14-03-0833
• http://doi.org/10.1093/database/bat008
• http://doi.org/10.1242/jcs.238659
• http://doi.org/10.1371/journal.pgen.1004875
• http://doi.org/10.1371/journal.pone.0052799
• http://doi.org/10.1155/2013/856325
• http://doi.org/10.1016/j.cub.2019.06.052
• http://doi.org/10.1093/nar/gkz1053
• http://doi.org/10.3389/fcell.2020.00509
• http://doi.org/10.1016/j.envpol.2020.115965
• http://doi.org/10.1007/s00203-018-1571-6

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• 4711351
• 4287346
• 3519685
• 3683052
• 3823935
• 3916650
• 3594985
• 3847961

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• {"domain"=>"self.science", "banned_by"=>nil, "media_embed"=>{}, "subreddit"=>"science", "selftext_html"=>"<!-- SC_OFF --><div class=\"md\"><p>Hi Reddit,</p>\n\n<p>October 15 – 25 is <a href=\"http://openaccessweek.org/\">Open Access Week</a> and this year's theme is "Open For Collaboration". PLOS authors Dr. John Ioannidis and Dr. Robert M. Kaplan are leading this AMA to discuss how more comprehensive reporting in scientific research can lead to more study replication, stronger statistical methods, and improvements to scientific standards, all of which are hallmarks of open access publishing.</p>\n\n<p>In <a href=\"http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001747\">"How to Make More Published Research True"</a>, an essay in <a href=\"http://journals.plos.org/plosmedicine\">PLOS Medicine</a>, Dr. John Ioannidis examined the factors behind false or exaggerated results in research and proposed solutions for improving the efficiency and value of scientific investigation.</p>\n\n<p>Dr. Robert M. Kaplan co-authored a <a href=\"http://journals.plos.org/plosone\">PLOS One</a> study, <a href=\"http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0132382\">"Likelihood of Null Effects of Large NHLBI Clinical Trials Has Increased over Time"</a>, which found that the number of null findings increased after the <a href=\"http://www.nhlbi.nih.gov/\">National Heart, Lung, and Blood Institute</a> adopted more transparent reporting standards.</p>\n\n<p>Here is a little more information about the participants for this week's PLOS Science Wednesday AMA:</p>\n\n<p>Dr. John Ioannidis is one of the two Directors of <a href=\"http://metrics.stanford.edu/\">Meta-Research Innovation Center at Stanford</a>. He also holds the C.F. Rehnborg Chair in Disease Prevention at <a href=\"https://www.stanford.edu/\">Stanford University</a>, and he is Professor of Medicine, and of Health Research and Policy, and Director of the <a href=\"http://prevention.stanford.edu/\">Stanford Prevention Research Center</a> at the School of Medicine and Director of the PhD program in Epidemiology and Clinical Research as well as Professor of Statistics at Stanford University School of Humanities and Sciences. Dr. Ioannidis has served as member of the editorial board of more than 20 major journals and he is also a member of the <a href=\"http://journals.plos.org/plosmedicine\">PLOS Medicine</a> and <a href=\"http://journals.plos.org/plosone\">PLOS ONE</a> editorial boards. His work has already been cited over 85,000 times in the scientific literature and there are currently more than 1,500 new citations to his work every month. His 2005 <a href=\"http://journals.plos.org/plosmedicine\">PLOS Medicine</a> paper on "<a href=\"http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.0020124\">Why most published research findings are false</a>" has been accessed 1.5 million times.</p>\n\n<p>Dr. Robert M. Kaplan served as Chief Science Officer at the <a href=\"http://www.ahrq.gov/\">U.S. Agency for Healthcare Research and Quality (AHRQ)</a> and Associate Director of the <a href=\"http://www.nih.gov/\">National Institutes of Health</a>, where he led the behavioral and social sciences programs. He was formerly the Distinguished Professor of Health Services and Medicine at <a href=\"http://www.ucla.edu/\">University of California, Los Angeles</a>, where he led the UCLA/RAND AHRQ health services training program and the UCLA/RAND CDC Prevention Research Center. He was Chair of the Department of Health Services from 2004 to 2009. From 1997 to 2004 he was Professor and Chair of the Department of Family and Preventive Medicine, at the <a href=\"https://ucsd.edu/\">University of California, San Diego</a>. He is a past president of several organizations, including the American Psychological Association Division of Health Psychology, Section J of the American Association for the Advancement of Science (Pacific), the International Society for Quality of Life Research, the Society for Behavioral Medicine, and the Academy of Behavioral Medicine Research. Kaplan is a former Editor-in-Chief of <a href=\"http://www.apa.org/pubs/journals/hea/\">Health Psychology</a> and of the <a href=\"http://www.springer.com/medicine/journal/12160\">Annals of Behavioral Medicine</a>. His 18 books and over 500 articles or chapters have been cited more than 28,000 times. Kaplan is a member of the <a href=\"http://nam.edu/\">National Academy of Medicine</a> (formerly the Institute of Medicine).</p>\n\n<p>We will be taking your questions at 1pm ET (10 am PT, 5 pm UTC), Ask Us Anything!</p>\n</div><!-- SC_ON -->", "selftext"=>"Hi Reddit,\n\n\nOctober 15 – 25 is [Open Access Week](http://openaccessweek.org/) and this year's theme is \"Open For Collaboration\". PLOS authors Dr. John Ioannidis and Dr. Robert M. Kaplan are leading this AMA to discuss how more comprehensive reporting in scientific research can lead to more study replication, stronger statistical methods, and improvements to scientific standards, all of which are hallmarks of open access publishing.\n\n\nIn [\"How to Make More Published Research True\"](http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001747), an essay in [PLOS Medicine](http://journals.plos.org/plosmedicine), Dr. John Ioannidis examined the factors behind false or exaggerated results in research and proposed solutions for improving the efficiency and value of scientific investigation.\n\n\nDr. Robert M. Kaplan co-authored a [PLOS One](http://journals.plos.org/plosone) study, [\"Likelihood of Null Effects of Large NHLBI Clinical Trials Has Increased over Time\"](http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0132382), which found that the number of null findings increased after the [National Heart, Lung, and Blood Institute](http://www.nhlbi.nih.gov/) adopted more transparent reporting standards.\n\n\nHere is a little more information about the participants for this week's PLOS Science Wednesday AMA:\n\n\nDr. John Ioannidis is one of the two Directors of [Meta-Research Innovation Center at Stanford](http://metrics.stanford.edu/). He also holds the C.F. Rehnborg Chair in Disease Prevention at [Stanford University](https://www.stanford.edu/), and he is Professor of Medicine, and of Health Research and Policy, and Director of the [Stanford Prevention Research Center](http://prevention.stanford.edu/) at the School of Medicine and Director of the PhD program in Epidemiology and Clinical Research as well as Professor of Statistics at Stanford University School of Humanities and Sciences. Dr. Ioannidis has served as member of the editorial board of more than 20 major journals and he is also a member of the [PLOS Medicine](http://journals.plos.org/plosmedicine) and [PLOS ONE](http://journals.plos.org/plosone) editorial boards. His work has already been cited over 85,000 times in the scientific literature and there are currently more than 1,500 new citations to his work every month. His 2005 [PLOS Medicine](http://journals.plos.org/plosmedicine) paper on \"[Why most published research findings are false](http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.0020124)\" has been accessed 1.5 million times.\n\n\nDr. Robert M. Kaplan served as Chief Science Officer at the [U.S. Agency for Healthcare Research and Quality (AHRQ)](http://www.ahrq.gov/) and Associate Director of the [National Institutes of Health](http://www.nih.gov/), where he led the behavioral and social sciences programs. He was formerly the Distinguished Professor of Health Services and Medicine at [University of California, Los Angeles](http://www.ucla.edu/), where he led the UCLA/RAND AHRQ health services training program and the UCLA/RAND CDC Prevention Research Center. He was Chair of the Department of Health Services from 2004 to 2009. From 1997 to 2004 he was Professor and Chair of the Department of Family and Preventive Medicine, at the [University of California, San Diego](https://ucsd.edu/). He is a past president of several organizations, including the American Psychological Association Division of Health Psychology, Section J of the American Association for the Advancement of Science (Pacific), the International Society for Quality of Life Research, the Society for Behavioral Medicine, and the Academy of Behavioral Medicine Research. Kaplan is a former Editor-in-Chief of [Health Psychology](http://www.apa.org/pubs/journals/hea/) and of the [Annals of Behavioral Medicine](http://www.springer.com/medicine/journal/12160). His 18 books and over 500 articles or chapters have been cited more than 28,000 times. Kaplan is a member of the [National Academy of Medicine](http://nam.edu/) (formerly the Institute of Medicine).\n\n\nWe will be taking your questions at 1pm ET (10 am PT, 5 pm UTC), Ask Us Anything!", "likes"=>nil, "suggested_sort"=>"confidence", "user_reports"=>[], "secure_media"=>nil, "link_flair_text"=>"Research Reproducibility AMA", "id"=>"3pmfis", "from_kind"=>nil, "gilded"=>0, "archived"=>true, "clicked"=>false, "report_reasons"=>nil, "author"=>"PLOSScienceWednesday", "media"=>nil, "score"=>632, "approved_by"=>nil, "over_18"=>false, "hidden"=>false, "preview"=>{"images"=>[{"source"=>{"url"=>"https://i.redditmedia.com/AN4dB6CgGk8dcxpvrF6BjWTYeIsNKzrP8VpwUW3GFIQ.jpg?s=acd23e918bdde37c984eb9f1f4aca33f", "width"=>90, "height"=>90}, "resolutions"=>[], "variants"=>{}, "id"=>"UqV5YFhcB3YtZVjiSQ0BNOXFRlNI1PHegkmp2EXupNg"}]}, "num_comments"=>71, "thumbnail"=>"self", "subreddit_id"=>"t5_mouw", "hide_score"=>false, "edited"=>1445432538.0, "link_flair_css_class"=>"ama2 med-ama", "author_flair_css_class"=>"AMA bio reward20", "downs"=>0, "secure_media_embed"=>{}, "saved"=>false, "removal_reason"=>nil, "post_hint"=>"self", "stickied"=>false, "from"=>nil, "is_self"=>true, "from_id"=>nil, "permalink"=>"/r/science/comments/3pmfis/plos_science_wednesday_hi_reddit_were_dr_john/?ref=search_posts", "locked"=>false, "name"=>"t3_3pmfis", "created"=>1445457619.0, "url"=>"https://www.reddit.com:80/r/science/comments/3pmfis/plos_science_wednesday_hi_reddit_were_dr_john/", "author_flair_text"=>"PLOS Science Wednesday Guest", "quarantine"=>false, "title"=>"PLOS Science Wednesday: Hi Reddit, we're Dr. John Ioannidis and Dr. Robert Kaplan, and we're here to discuss the importance of improved reporting in scholarly research for Open Access Week — Ask Us Anything!", "created_utc"=>1445428819.0, "distinguished"=>nil, "mod_reports"=>[], "visited"=>false, "num_reports"=>nil, "ups"=>632}

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/387139", "https://ndownloader.figshare.com/files/387153", "https://ndownloader.figshare.com/files/387173", "https://ndownloader.figshare.com/files/387188", "https://ndownloader.figshare.com/files/387201", "https://ndownloader.figshare.com/files/387215", "https://ndownloader.figshare.com/files/387230", "https://ndownloader.figshare.com/files/387239", "https://ndownloader.figshare.com/files/387248"], "description"=>"<div><h3>Background</h3><p>Genome-wide expression data of gene microarrays can be used to infer gene networks. At a cellular level, a gene network provides a picture of the modules in which genes are densely connected, and of the hub genes, which are highly connected with other genes. A gene network is useful to identify the genes involved in the same pathway, in a protein complex or that are co-regulated. In this study, we used different methods to find gene networks in the ciliate <em>Tetrahymena thermophila</em>, and describe some important properties of this network, such as modules and hubs.</p> <h3>Methodology/Principal Findings</h3><p>Using 67 single channel microarrays, we constructed the <em>Tetrahymena</em> gene network (TGN) using three methods: the Pearson correlation coefficient (PCC), the Spearman correlation coefficient (SCC) and the context likelihood of relatedness (CLR) algorithm. The accuracy and coverage of the three networks were evaluated using four conserved protein complexes in yeast. The CLR network with a Z-score threshold 3.49 was determined to be the most robust. The TGN was partitioned, and 55 modules were found. In addition, analysis of the arbitrarily determined 1200 hubs showed that these hubs could be sorted into six groups according to their expression profiles. We also investigated human disease orthologs in <em>Tetrahymena</em> that are missing in yeast and provide evidence indicating that some of these are involved in the same process in <em>Tetrahymena</em> as in human.</p> <h3>Conclusions/Significance</h3><p>This study constructed a <em>Tetrahymena</em> gene network, provided new insights to the properties of this biological network, and presents an important resource to study <em>Tetrahymena</em> genes at the pathway level.</p> </div>", "links"=>[], "tags"=>["ciliate"], "article_id"=>136443, "categories"=>["Genetics", "Microbiology"], "users"=>["Jie Xiong", "Dongxia Yuan", "Jeffrey S. Fillingham", "Jyoti Garg", "Xingyi Lu", "Yue Chang", "Yifan Liu", "Chengjie Fu", "Ronald E. Pearlman", "Wei Miao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020124.s001", "https://dx.doi.org/10.1371/journal.pone.0020124.s002", "https://dx.doi.org/10.1371/journal.pone.0020124.s003", "https://dx.doi.org/10.1371/journal.pone.0020124.s004", "https://dx.doi.org/10.1371/journal.pone.0020124.s005", "https://dx.doi.org/10.1371/journal.pone.0020124.s006", "https://dx.doi.org/10.1371/journal.pone.0020124.s007", "https://dx.doi.org/10.1371/journal.pone.0020124.s008", "https://dx.doi.org/10.1371/journal.pone.0020124.s009"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Gene_Network_Landscape_of_the_Ciliate_Tetrahymena_thermophila_/136443", "title"=>"Gene Network Landscape of the Ciliate <em>Tetrahymena thermophila</em>", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2011-05-26 01:47:23"}
• {"files"=>["https://ndownloader.figshare.com/files/771203"], "description"=>"<p>For the CLR method, the cutoff value represents the Z-score with a minimal value of 3.34 corresponding to the 60% confidence level of the FDR test; for the PCC and SCC methods, the cutoff value represents the correlation coefficient. The minimal correlation coefficient is 0.6.</p>", "links"=>[], "tags"=>["node", "cutoff"], "article_id"=>441565, "categories"=>["Genetics", "Microbiology"], "users"=>["Jie Xiong", "Dongxia Yuan", "Jeffrey S. Fillingham", "Jyoti Garg", "Xingyi Lu", "Yue Chang", "Yifan Liu", "Chengjie Fu", "Ronald E. Pearlman", "Wei Miao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020124.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_node_and_edge_number_against_cutoff_values_for_three_methods_/441565", "title"=>"The node and edge number against cutoff values for three methods.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-05-26 00:26:05"}
• {"files"=>["https://ndownloader.figshare.com/files/771288"], "description"=>"<p>The F-score against the cutoff values (X-axis) of three methods for each protein complex is presented. Blue, CLR method; Pink, PCC method; Green, SCC method. For the CLR method, the cutoff value means the different confidence levels of the FDR test; for the PCC and SCC methods, the cutoff values represent the correlation coefficient.</p>", "links"=>[], "tags"=>["methods"], "article_id"=>441655, "categories"=>["Genetics", "Microbiology"], "users"=>["Jie Xiong", "Dongxia Yuan", "Jeffrey S. Fillingham", "Jyoti Garg", "Xingyi Lu", "Yue Chang", "Yifan Liu", "Chengjie Fu", "Ronald E. Pearlman", "Wei Miao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020124.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overall_performance_of_three_methods_for_four_protein_complexes_/441655", "title"=>"Overall performance of three methods for four protein complexes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-05-26 00:27:35"}
• {"files"=>["https://ndownloader.figshare.com/files/771464"], "description"=>"<p>A, KEGG annotated <i>Tetrahymena</i> proteasome complex (<a href=\"http://www.kegg.jp/kegg-bin/show_pathway?tet03050\" target=\"_blank\">http://www.kegg.jp/kegg-bin/show_pathway?tet03050</a>); B, Silver stained gel of a pull down experiment using Dss1 (Rpn15) as bait that identifies proteins of the <i>Tetrahymena</i> proteasome; C, The network of the possible <i>Tetrahymena</i> proteasome complex.</p>", "links"=>[], "tags"=>["components", "proteasome"], "article_id"=>441829, "categories"=>["Genetics", "Microbiology"], "users"=>["Jie Xiong", "Dongxia Yuan", "Jeffrey S. Fillingham", "Jyoti Garg", "Xingyi Lu", "Yue Chang", "Yifan Liu", "Chengjie Fu", "Ronald E. Pearlman", "Wei Miao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020124.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Possible_components_of_the_Tetrahymena_proteasome_complex_/441829", "title"=>"Possible components of the <i>Tetrahymena</i> proteasome complex.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-05-26 00:30:29"}
• {"files"=>["https://ndownloader.figshare.com/files/771557"], "description"=>"<p>The X-axis indicates the gained partners (each represents an edge) of genes, the value was Log2 transformed. The Y-axis indicates the frequency of gained partners number, also <i>Log2</i> transformed.</p>", "links"=>[], "tags"=>["gained", "partners", "genes"], "article_id"=>441915, "categories"=>["Genetics", "Microbiology"], "users"=>["Jie Xiong", "Dongxia Yuan", "Jeffrey S. Fillingham", "Jyoti Garg", "Xingyi Lu", "Yue Chang", "Yifan Liu", "Chengjie Fu", "Ronald E. Pearlman", "Wei Miao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020124.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_distribution_of_the_gained_partners_number_of_genes_in_TGN_/441915", "title"=>"The distribution of the gained partners number of genes in TGN.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-05-26 00:31:55"}
• {"files"=>["https://ndownloader.figshare.com/files/771636"], "description"=>"<p>The heatmap was clustered by Euclidean distance of expression. The levels of expression are illustrated by different grades of color as determined from microarray data indicated along the top (from left to right). The color scale is as follows: dark color, low expression; light color, high expression. Levels of expression were obtained for 20 points in time during three physiological/developmental stages of the life cycle of <i>Tetrahymena</i>: For growing cells, L-l, L-m and L-h correspond to ∼1×10⁵ cells/ml, ∼3.5×10⁵ cells/ml and ∼1×10⁶ cells/ml, respectively. For measurements of expression during starvation, ∼2×10⁵ cells/ml were collected at intervals of 0, 3, 6, 9, 12, 15 and 24 hours (referred to as S-0, S-3, S-6, S-9, S-12, S-15 and S-24, respectively). For measurements of expression during conjugation, equal volumes of B2086 and CU428 cells were mixed following 18 h of starvation, and samples were collected at intervals of 0, 2, 4, 6, 8, 10, 12, 14, 16 and 18 h after mixing (referred to as C-0, C-2, C-4, C-6, C-8, C-10, C-12, C-14, C-16 and C-18, respectively). The 1,200 genes were sorted into six groups according to clustering analysis.</p>", "links"=>[], "tags"=>["heatmap", "1200", "hub", "genes"], "article_id"=>441995, "categories"=>["Genetics", "Microbiology"], "users"=>["Jie Xiong", "Dongxia Yuan", "Jeffrey S. Fillingham", "Jyoti Garg", "Xingyi Lu", "Yue Chang", "Yifan Liu", "Chengjie Fu", "Ronald E. Pearlman", "Wei Miao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020124.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_heatmap_of_the_1200_hub_genes_in_TGN_/441995", "title"=>"The heatmap of the 1200 hub genes in TGN.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-05-26 00:33:15"}
• {"files"=>["https://ndownloader.figshare.com/files/771755"], "description"=>"<p>The modules are named by the gene numbers in descending order. GO ANNO NO, indicates the number of GO annotated genes; GO ANNO PER, indicates the percentage of GO annotated genes; BP, biological process; Ortho, orthologs with other eukaryotes (see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0020124#s4\" target=\"_blank\">Materials and Methods</a>).</p>", "links"=>[], "tags"=>["21", "modules", "containing", "100", "genes"], "article_id"=>442112, "categories"=>["Genetics", "Microbiology"], "users"=>["Jie Xiong", "Dongxia Yuan", "Jeffrey S. Fillingham", "Jyoti Garg", "Xingyi Lu", "Yue Chang", "Yifan Liu", "Chengjie Fu", "Ronald E. Pearlman", "Wei Miao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0020124.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Detailed_information_of_21_modules_containing_more_than_100_genes_in_the_TGN_/442112", "title"=>"Detailed information of 21 modules containing more than 100 genes in the TGN.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-05-26 00:35:12"}

PMC Usage Stats | Further Information

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• {"unique-ip"=>"9", "full-text"=>"9", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2020", "month"=>"6"}
• {"unique-ip"=>"11", "full-text"=>"14", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"9", "cited-by"=>"0", "year"=>"2020", "month"=>"7"}
• {"unique-ip"=>"3", "full-text"=>"4", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2020", "month"=>"8"}
• {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"9"}
• {"unique-ip"=>"9", "full-text"=>"8", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"10"}
• {"unique-ip"=>"5", "full-text"=>"3", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"11"}
• {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"12"}
• {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2021", "month"=>"1"}

Relative Metric

{"start_date"=>"2011-01-01T00:00:00Z", "end_date"=>"2011-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[304, 568, 702, 818, 927, 1027, 1118, 1206, 1285, 1357, 1427, 1500, 1564, 1636, 1705, 1773, 1840, 1909, 1974, 2039, 2106, 2170, 2234, 2296, 2358, 2423, 2484, 2546, 2606, 2673, 2734, 2795, 2857, 2921, 2984, 3046, 3100]}, {"subject_area"=>"/Biology and life sciences/Biochemistry", "average_usage"=>[290, 559, 698, 813, 927, 1028, 1121, 1206, 1289, 1360, 1433, 1501, 1569, 1637, 1707, 1774, 1841, 1911, 1974, 2038, 2103, 2161, 2219, 2280, 2345, 2406, 2466, 2529, 2592, 2654, 2713, 2772, 2835, 2893, 2954, 3020, 3071]}, {"subject_area"=>"/Biology and life sciences/Organisms", "average_usage"=>[316, 571, 699, 812, 915, 1008, 1095, 1180, 1255, 1319, 1393, 1461, 1528, 1595, 1662, 1729, 1802, 1868, 1937, 1997, 2062, 2130, 2192, 2254, 2324, 2386, 2450, 2510, 2579, 2642, 2716, 2778, 2842, 2908, 2979, 3042, 3095]}, {"subject_area"=>"/Computer and information sciences", "average_usage"=>[355, 609, 735, 840, 944, 1029, 1109, 1193, 1255, 1320, 1391, 1469, 1540, 1608, 1683, 1753, 1824, 1905, 1967, 2042, 2117, 2189, 2240, 2300, 2392, 2452, 2509, 2569, 2635, 2710, 2772, 2846, 2882, 2956, 3014, 3086, 3139]}, {"subject_area"=>"/Computer and information sciences/Network analysis", "average_usage"=>[429, 735, 900, 1007, 1119, 1213, 1298, 1390, 1459, 1528, 1611, 1697, 1774, 1859, 1932, 2001, 2114, 2189, 2279, 2342, 2389, 2460, 2561, 2642, 2696, 2770, 2852, 2915, 2972, 3082, 3187, 3243, 3317, 3445, 3552, 3609, 3664]}]}

F1000Prime