Causal Modeling Using Network Ensemble Simulations of Genetic and Gene Expression Data Predicts Genes Involved in Rheumatoid Arthritis
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{"title"=>"Causal modeling using network ensemble simulations of genetic and gene expression data predicts genes involved in rheumatoid arthritis", "type"=>"journal", "authors"=>[{"first_name"=>"Heming", "last_name"=>"Xing", "scopus_author_id"=>"57196934838"}, {"first_name"=>"Paul D.", "last_name"=>"McDonagh", "scopus_author_id"=>"36480262800"}, {"first_name"=>"Jadwiga", "last_name"=>"Bienkowska", "scopus_author_id"=>"56048068300"}, {"first_name"=>"Tanya", "last_name"=>"Cashorali", "scopus_author_id"=>"8338394000"}, {"first_name"=>"Karl", "last_name"=>"Runge", "scopus_author_id"=>"47161448400"}, {"first_name"=>"Robert E.", "last_name"=>"Miller", "scopus_author_id"=>"57195837743"}, {"first_name"=>"Dave", "last_name"=>"DeCaprio", "scopus_author_id"=>"8773007600"}, {"first_name"=>"Bruce", "last_name"=>"Church", "scopus_author_id"=>"16686069800"}, {"first_name"=>"Ronenn", "last_name"=>"Roubenoff", "scopus_author_id"=>"7004810432"}, {"first_name"=>"Iya G.", "last_name"=>"Khalil", "scopus_author_id"=>"8254037300"}, {"first_name"=>"John", "last_name"=>"Carulli", "scopus_author_id"=>"6601935541"}], "year"=>2011, "source"=>"PLoS Computational Biology", "identifiers"=>{"issn"=>"1553734X", "scopus"=>"2-s2.0-79953670434", "sgr"=>"79953670434", "pui"=>"361550326", "isbn"=>"1553-7358 (Linking)", "pmid"=>"21423713", "doi"=>"10.1371/journal.pcbi.1001105"}, "id"=>"ac9e6af1-414a-3200-9537-f762a72aaa02", "abstract"=>"Tumor necrosis factor α (TNF-α) is a key regulator of inflammation and rheumatoid arthritis (RA). TNF-α blocker therapies can be very effective for a substantial number of patients, but fail to work in one third of patients who show no or minimal response. It is therefore necessary to discover new molecular intervention points involved in TNF-α blocker treatment of rheumatoid arthritis patients. We describe a data analysis strategy for predicting gene expression measures that are critical for rheumatoid arthritis using a combination of comprehensive genotyping, whole blood gene expression profiles and the component clinical measures of the arthritis Disease Activity Score 28 (DAS28) score. Two separate network ensembles, each comprised of 1024 networks, were built from molecular measures from subjects before and 14 weeks after treatment with TNF-α blocker. The network ensemble built from pre-treated data captures TNF-α dependent mechanistic information, while the ensemble built from data collected under TNF-α blocker treatment captures TNF-α independent mechanisms. In silico simulations of targeted, personalized perturbations of gene expression measures from both network ensembles identify transcripts in three broad categories. Firstly, 22 transcripts are identified to have new roles in modulating the DAS28 score; secondly, there are 6 transcripts that could be alternative targets to TNF-α blocker therapies, including CD86--a component of the signaling axis targeted by Abatacept (CTLA4-Ig), and finally, 59 transcripts that are predicted to modulate the count of tender or swollen joints but not sufficiently enough to have a significant impact on DAS28.", "link"=>"http://www.mendeley.com/research/causal-modeling-using-network-ensemble-simulations-genetic-gene-expression-data-predicts-genes-invol", "reader_count"=>113, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>7, "Researcher"=>57, "Student > Ph. D. Student"=>18, "Other"=>15, "Student > Master"=>4, "Student > Bachelor"=>6, "Lecturer > Senior Lecturer"=>1, "Professor"=>5}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>7, "Researcher"=>57, "Student > Ph. D. Student"=>18, "Other"=>15, "Student > Master"=>4, "Student > Bachelor"=>6, "Lecturer > Senior Lecturer"=>1, "Professor"=>5}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Agricultural and Biological Sciences"=>60, "Business, Management and Accounting"=>3, "Chemistry"=>2, "Computer Science"=>10, "Economics, Econometrics and Finance"=>1, "Engineering"=>2, "Biochemistry, Genetics and Molecular Biology"=>11, "Mathematics"=>1, "Medicine and Dentistry"=>17, "Neuroscience"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>1, "Linguistics"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>17}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>2}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Engineering"=>{"Engineering"=>2}, "Chemistry"=>{"Chemistry"=>2}, "Neuroscience"=>{"Neuroscience"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>60}, "Computer Science"=>{"Computer Science"=>10}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>3}, "Linguistics"=>{"Linguistics"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>11}}, "reader_count_by_country"=>{"Greece"=>1, "Canada"=>1, "Argentina"=>1, "Belgium"=>1, "United States"=>9, "Japan"=>1, "United Kingdom"=>2, "France"=>1, "India"=>1}, "group_count"=>11}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/396320", "https://ndownloader.figshare.com/files/396350", "https://ndownloader.figshare.com/files/396379", "https://ndownloader.figshare.com/files/396399", "https://ndownloader.figshare.com/files/396437", "https://ndownloader.figshare.com/files/396450", "https://ndownloader.figshare.com/files/396466"], "description"=>"<div><p>Tumor necrosis factor α (TNF-α) is a key regulator of inflammation and rheumatoid arthritis (RA). TNF-α blocker therapies can be very effective for a substantial number of patients, but fail to work in one third of patients who show no or minimal response. It is therefore necessary to discover new molecular intervention points involved in TNF-α blocker treatment of rheumatoid arthritis patients. We describe a data analysis strategy for predicting gene expression measures that are critical for rheumatoid arthritis using a combination of comprehensive genotyping, whole blood gene expression profiles and the component clinical measures of the arthritis Disease Activity Score 28 (DAS28) score. Two separate network ensembles, each comprised of 1024 networks, were built from molecular measures from subjects before and 14 weeks after treatment with TNF-α blocker. The network ensemble built from pre-treated data captures TNF-α dependent mechanistic information, while the ensemble built from data collected under TNF-α blocker treatment captures TNF-α independent mechanisms. <em>In silico</em> simulations of targeted, personalized perturbations of gene expression measures from both network ensembles identify transcripts in three broad categories. Firstly, 22 transcripts are identified to have new roles in modulating the DAS28 score; secondly, there are 6 transcripts that could be alternative targets to TNF-α blocker therapies, including CD86 - a component of the signaling axis targeted by Abatacept (CTLA4-Ig), and finally, 59 transcripts that are predicted to modulate the count of tender or swollen joints but not sufficiently enough to have a significant impact on DAS28.</p></div>", "links"=>[], "tags"=>["causal", "modeling", "ensemble", "simulations", "genes", "rheumatoid", "arthritis"], "article_id"=>138285, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1001105.s001", "https://dx.doi.org/10.1371/journal.pcbi.1001105.s002", "https://dx.doi.org/10.1371/journal.pcbi.1001105.s003", "https://dx.doi.org/10.1371/journal.pcbi.1001105.s004", "https://dx.doi.org/10.1371/journal.pcbi.1001105.s005", "https://dx.doi.org/10.1371/journal.pcbi.1001105.s006", "https://dx.doi.org/10.1371/journal.pcbi.1001105.s007"], "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Causal_Modeling_Using_Network_Ensemble_Simulations_of_Genetic_and_Gene_Expression_Data_Predicts_Genes_Involved_in_Rheumatoid_Arthritis/138285", "title"=>"Causal Modeling Using Network Ensemble Simulations of Genetic and Gene Expression Data Predicts Genes Involved in Rheumatoid Arthritis", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2011-03-10 02:18:05"}
  • {"files"=>["https://ndownloader.figshare.com/files/792102"], "description"=>"<p>Plots of simulated number of tender joints, swollen joints, pain and C-reactive protein concentrations in response to a 10-fold knockdown in gene expression of <i>CD86</i>, the target of abatacept (CTLA4-Ig), in A. pretreated subjects and B. TNF-α blocker treated subjects. The modulation of tender joints is only predicted in TNF-α treated patients, suggesting both a mechanism that is independent of TNF-α signaling that could be exploited for subjects that do not respond well to TNF-α blocker therapies.</p>", "links"=>[], "tags"=>["swollen", "counts", "treated"], "article_id"=>462459, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.g006", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Modulation_CD86_predicted_to_affect_both_tender_and_swollen_joint_counts_in_TNF_treated_patients_/462459", "title"=>"Modulation <i>CD86</i> predicted to affect both tender and swollen joint counts in TNF-α treated patients.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-03-10 00:40:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/791737"], "description"=>"<p>Plots of simulated number of tender joints, swollen joints, pain and C-reactive protein concentrations in response to a 10-fold knockdown in gene expression of cytokine <i>IL32</i> in A. pretreated subjects and B. TNF-α blocker treated subjects. The effects are only predicted in pre-treated patients, suggesting a dependence on TNF-α signaling. The largest predicted effect is to modulate the number of swollen joints.</p>", "links"=>[], "tags"=>["knockdown", "modulates", "swollen"], "article_id"=>462091, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.g003", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_10_fold_knockdown_of_IL32_modulates_number_of_swollen_joints_/462091", "title"=>"10-fold knockdown of <i>IL32</i> modulates number of swollen joints.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-03-10 00:34:51"}
  • {"files"=>["https://ndownloader.figshare.com/files/792501"], "description"=>"<p>In <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001105#pcbi-1001105-t003\" target=\"_blank\">Tables 3</a> and <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001105#pcbi-1001105-t004\" target=\"_blank\">4</a>, transcripts are potential alternatives to TNF-α therapies and have known dependencies on TNF-α or are proteins that could be targeted with a small molecule and their predicted modulation might be expected to modulate DAS28 or joint health (<i>p</i><0.05).</p>", "links"=>[], "tags"=>["transcripts", "post-treatment"], "article_id"=>462856, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.t003", "stats"=>{"downloads"=>3, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Category_2_Transcripts_from_the_post_treatment_model_/462856", "title"=>"Category 2 Transcripts from the post-treatment model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-03-10 00:47:36"}
  • {"files"=>["https://ndownloader.figshare.com/files/792218"], "description"=>"<p>Plots of simulated number of tender joints, swollen joints, pain and C-reactive protein concentrations in response to a 10-fold knockdown in gene expression of <i>RAP2C</i>, a recently described ras G-protein, in A. pretreated subjects and B. TNF-α blocker treated subjects. The simulations suggest that this novel gene can modulate both tender and swollen joint count in TNF-α treated subjects. <i>RAP2C</i> may provide insight into novel TNF-α independent signaling pathways in RA.</p>", "links"=>[], "tags"=>["modulate", "swollen", "counts", "treated"], "article_id"=>462578, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.g007", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_RAP2C_predicted_to_modulate_both_tender_and_swollen_joint_counts_in_TNF_treated_patients_/462578", "title"=>"<i>RAP2C</i> predicted to modulate both tender and swollen joint counts in TNF-α treated patients.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-03-10 00:42:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/791440"], "description"=>"<p>A. Genetic, gene expression and phenotypic data are prepared for modeling by formatting followed by investigation to select the appropriate data transformation for the particular data type. Confounding factors and other explanatory variables are considered and modeled if appropriate. B. Likely fragments for network reconstruction are identified by scoring all 2-, 3- and 4-variable combinations with the constraint that SNPs are causally upstream. There are too many scored combinations to consider all during network reconstruction. The fragments that had the most likely Bayesian scores for each individual variable were identified and retained for network reconstruction. C. Parallel global network sampling constructs an ensemble of 1024 network structures that explain the data. The probabilistic directionality computed by the Bayesian framework allows inferences to be made about what lies upstream and downstream of particular phenotypic variables D. Diversity in network structures identified during network reconstruction captures uncertainty in the model. Hypotheses are extracted from the network ensemble by completing Monte Carlo simulations of “what-if” scenarios. Down-regulating the blue transcript would be expected to impact both TJ and SJ, while leaving CRP unchanged. The change in these phenotypic parameters would further predict <i>reactive</i> transcription changes in the liver. The separation of upstream and downstream components can identify potential intervention points and markers.</p>", "links"=>[], "tags"=>["bayesian", "monte", "carlo"], "article_id"=>461798, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.g001", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Schematic_of_Bayesian_network_reverse_engineering_and_Monte_Carlo_simulation_/461798", "title"=>"Schematic of Bayesian network reverse engineering and Monte Carlo simulation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-03-10 00:29:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/792303"], "description"=>"<p>Plots of simulated number of tender joints, swollen joints, pain and C-reactive protein concentrations in response to a 10-fold knockdown in gene expression of <i>GON4L</i>, recently described as a novel factor in B-cell differentiation, in A. pretreated subjects and B. TNF-α blocker treated subjects. The simulations suggest that this novel gene can modulate both tender and swollen joint count in TNF-α treated subjects. <i>GON4L</i> may provide insight into novel TNF-α independent signaling pathways in RA.</p>", "links"=>[], "tags"=>["modulate", "swollen", "treated"], "article_id"=>462659, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.g008", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_GON4L_predicted_modulate_both_tender_and_swollen_joint_count_in_TNF_treated_patients_/462659", "title"=>"<i>GON4L</i> predicted modulate both tender and swollen joint count in TNF-α treated patients.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-03-10 00:44:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/792634"], "description"=>"<p>Significantly enriched immune response related GO terms for transcripts from untreated model.</p>", "links"=>[], "tags"=>["enriched", "transcripts", "untreated"], "article_id"=>462993, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.t007", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Significantly_enriched_immune_response_related_GO_terms_for_transcripts_from_untreated_model_/462993", "title"=>"Significantly enriched immune response related GO terms for transcripts from untreated model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-03-10 00:49:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/792589"], "description"=>"<p>Transcripts predicted to impact joint health (<i>p</i><0.05) but not DAS28 (<i>p</i>>0.05)</p>", "links"=>[], "tags"=>["transcripts", "pre-treatment"], "article_id"=>462946, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.t006", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Category_3_Transcripts_from_the_pre_treatment_model_/462946", "title"=>"Category 3 Transcripts from the pre-treatment model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-03-10 00:49:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/791964"], "description"=>"<p>Plots of simulated number of tender joints, swollen joints, pain and C-reactive protein concentrations in response to a 10-fold knockdown in gene expression of tryptophanyl-tRNA synthetase, <i>WARS</i>, in A. pretreated subjects and B. TNF-α blocker treated subjects. The modulation of tender joints is only predicted in pre-treated patients, suggesting a dependence on TNF-α signaling.</p>", "links"=>[], "tags"=>["joints", "modulated", "pre-treated", "patients"], "article_id"=>462315, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.g005", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Tender_joints_predicted_to_be_modulated_by_WARS_in_pre_treated_patients_only_/462315", "title"=>"Tender joints predicted to be modulated by <i>WARS</i> in pre-treated patients only.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-03-10 00:38:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/791608"], "description"=>"<p>A. Snapshot of the network ensemble at 2.5% consensus topology generated from pre-treated subjects. Pain does not appear to be controlled by measures extracted from whole blood mRNA profiling in pre-treated subjects. B. Snapshot of the network consensus topology at 2.5% consensus generated from TNF-α blocker treated data.</p>", "links"=>[], "tags"=>["topology", "ensembles", "pre-treated", "blocker", "treated"], "article_id"=>461962, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.g002", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Consensus_topology_of_network_ensembles_for_pre_treated_and_TNF_945_blocker_treated_data_/461962", "title"=>"Consensus topology of network ensembles for pre-treated and TNF-α blocker treated data.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-03-10 00:32:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/792458"], "description"=>"<p>Category 1 Transcripts from the pre-treatment model.</p>", "links"=>[], "tags"=>["transcripts", "pre-treatment"], "article_id"=>462818, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.t002", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Category_1_Transcripts_from_the_pre_treatment_model_/462818", "title"=>"Category 1 Transcripts from the pre-treatment model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-03-10 00:46:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/791845"], "description"=>"<p>Plots of simulated number of tender joints, swollen joints, pain and C-reactive protein concentrations in response to a 10-fold knockdown in gene expression of ceramide synthase, <i>LASS5</i>, in A. pretreated subjects and B. TNF-α blocker treated subjects. The modulation of swollen joints is only predicted in pre-treated patients, suggesting a dependence on TNF-α signaling.</p>", "links"=>[], "tags"=>["joints", "modulated", "pre-treated", "patients"], "article_id"=>462203, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.g004", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Swollen_joints_predicted_to_be_modulated_by_LASS5_in_pre_treated_patients_only_/462203", "title"=>"Swollen joints predicted to be modulated by <i>LASS5</i> in pre-treated patients only.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-03-10 00:36:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/792709"], "description"=>"<p>In <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001105#pcbi-1001105-t005\" target=\"_blank\">Tables 5</a> and <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001105#pcbi-1001105-t006\" target=\"_blank\">6</a>, transcripts are predicted to impact joint health (<i>p</i><0.05) but not DAS28 (<i>p</i>>0.05).</p>", "links"=>[], "tags"=>["transcripts", "post-treatment"], "article_id"=>463068, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.t005", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Category_3_Transcripts_from_the_post_treatment_model_/463068", "title"=>"Category 3 Transcripts from the post-treatment model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-03-10 00:51:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/792546"], "description"=>"<p>In <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001105#pcbi-1001105-t001\" target=\"_blank\">Tables 1</a> and <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001105#pcbi-1001105-t002\" target=\"_blank\">2</a>, these transcripts have a predicted novel role in either untreated or treated RA, are not directly related to TNFα biology and have statistically significant impacts on DAS28 or joint health (denoted by X, <i>p</i><0.05).</p>", "links"=>[], "tags"=>["transcripts", "post-treatment"], "article_id"=>462902, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.t001", "stats"=>{"downloads"=>2, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Category_1_Transcripts_from_the_post_treatment_model_/462902", "title"=>"Category 1 Transcripts from the post-treatment model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-03-10 00:48:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/792414"], "description"=>"<p>Significantly enriched immune response related GO terms for transcripts from anti-TNF-α treated model.</p>", "links"=>[], "tags"=>["enriched", "transcripts", "treated"], "article_id"=>462774, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.t008", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Significantly_enriched_immune_response_related_GO_terms_for_transcripts_from_anti_TNF_945_treated_model_/462774", "title"=>"Significantly enriched immune response related GO terms for transcripts from anti-TNF-α treated model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-03-10 00:46:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/792673"], "description"=>"<p>Category 2 Transcripts from the pre-treatment model.</p>", "links"=>[], "tags"=>["transcripts", "pre-treatment"], "article_id"=>463026, "categories"=>["Genetics", "Medicine", "Immunology", "Biological Sciences"], "users"=>["Heming Xing", "Paul D. McDonagh", "Jadwiga Bienkowska", "Tanya Cashorali", "Karl Runge", "Robert E. Miller", "Dave DeCaprio", "Bruce Church", "Ronenn Roubenoff", "Iya G. Khalil", "John Carulli"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1001105.t004", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Category_2_Transcripts_from_the_pre_treatment_model_/463026", "title"=>"Category 2 Transcripts from the pre-treatment model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-03-10 00:50:26"}

PMC Usage Stats | Further Information

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Relative Metric

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