The Effect of Ongoing Exposure Dynamics in Dose Response Relationships
Publication Date
June 05, 2009
Journal
PLOS Computational Biology
Authors
Josep M. Pujol, Joseph E. Eisenberg, Charles N. Haas & James S. Koopman
Volume
5
Issue
6
Pages
e1000399
DOI
https://dx.plos.org/10.1371/journal.pcbi.1000399
Publisher URL
http://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1000399
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/19503605
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2685010
Europe PMC
http://europepmc.org/abstract/MED/19503605
Web of Science
000268436100007
Scopus
67650860432
Mendeley
http://www.mendeley.com/research/effect-ongoing-exposure-dynamics-dose-response-relationships
Events
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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/896140"], "description"=>"<p>The estimated parameters are for the Exponential model, for the Beta-Poisson model [31]\n and for the Cumulative Dose model. (*) The\n dose in the original trial was administered in concentrations, to\n work with discrete pathogens as required by the Cumulative Dose\n model, we assumed that the concentration of\n 9×10<sup>−2</sup> is equivalent to 9\n pathogens. As a consequence the concentration of\n 9×10<sup>−3</sup> could not be tested since\n it is a fraction of a pathogen. The probability of infection for a\n single pathogen is 10<sup>−3</sup>. This assumption is\n only required by the Cumulative Dose model.</p>", "links"=>[], "tags"=>["rotavirus", "compared", "beta-poisson", "and", "cumulative"], "article_id"=>566592, "categories"=>["Immunology", "Computational Biology", "Mathematics", "Medicine"], "users"=>["Josep M. Pujol", "Joseph E. Eisenberg", "Charles N. Haas", "James S. Koopman"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000399.t003", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Probability_of_infection_from_experimental_data_for_Rotavirus_compared_to_the_the_Exponential_Beta_Poisson_and____Cumulative_Dose_models_/566592", "title"=>"Probability of infection from experimental data for Rotavirus () compared to the the Exponential, Beta-Poisson and\n Cumulative Dose models.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-21 05:46:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/895579"], "description"=>"<p>The estimated parameters are for the Exponential model <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000399#pcbi.1000399-Eisenberg1\" target=\"_blank\">[3]</a> and for the Cumulative Dose model.</p>", "links"=>[], "tags"=>["curves", "exponential", "cumulative", "compared", "dataset", "poliovirus"], "article_id"=>566029, "categories"=>["Immunology", "Computational Biology", "Mathematics", "Medicine"], "users"=>["Josep M. Pujol", "Joseph E. Eisenberg", "Charles N. Haas", "James S. Koopman"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000399.g004", "stats"=>{"downloads"=>0, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Dose_response_curves_based_on_the_Exponential_Model_and_the_Cumulative_Dose_model_compared_to_the_experimental_dataset_for_Poliovirus____type_1_squares_/566029", "title"=>"Dose-response curves based on the Exponential Model () and the Cumulative Dose model () compared to the experimental dataset for Poliovirus\n type 1 (squares).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 05:43:28"}
  • {"files"=>["https://ndownloader.figshare.com/files/895301"], "description"=>"<p>Each line represents an individual replicate with the same parameter set\n (100 in total). The fraction of replicates in which the number of\n pathogens diverge towards infinity, as opposed to going extinct, is\n equivalent to the probability of infection\n (<i>p<sub>inf</sub></i>) for the dose (main graph, and for the insets a) and b) respectively). Temporal\n exposure length is fixed at\n <i>T<sub>e</sub></i> = 1\n hour. Probability of infection is 0.67, 0.02 and 0.98 for the main\n graph, the inset a), and the inset b) respectively.</p>", "links"=>[], "tags"=>["pathogens", "characteristic", "parameter"], "article_id"=>565755, "categories"=>["Immunology", "Computational Biology", "Mathematics", "Medicine"], "users"=>["Josep M. Pujol", "Joseph E. Eisenberg", "Charles N. Haas", "James S. Koopman"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000399.g001", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolution_of_the_number_of_pathogens_over_time_for_a_characteristic____parameter_set_/565755", "title"=>"Evolution of the number of pathogens over time for a characteristic\n parameter set .", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 05:41:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/896061"], "description"=>"<p>The estimated parameters are for the Exponential model <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000399#pcbi.1000399-Eisenberg1\" target=\"_blank\">[3]</a> and for the Cumulative Dose model.</p>", "links"=>[], "tags"=>["polivirus", "compared", "probability", "the", "exponential", "cumulative"], "article_id"=>566508, "categories"=>["Immunology", "Computational Biology", "Mathematics", "Medicine"], "users"=>["Josep M. Pujol", "Joseph E. Eisenberg", "Charles N. Haas", "James S. Koopman"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000399.t001", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Probability_of_infection_from_experimental_data_for_Polivirus_type_1_compared_to_the_probability_of_infection_based_on_the____Exponential_model_and_the_Cumulative_Dose_model_/566508", "title"=>"Probability of infection from experimental data for Polivirus type 1 () compared to the probability of infection based on the\n Exponential model () and the Cumulative Dose model ().", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-21 05:46:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/895406"], "description"=>"<p>The distribution of probabilities if would be given the parameters of the system are . The dashed white line is the separatrix of the\n deterministic version of the model (see subsection Deterministic\n Analysis); if the system were deterministic once inoculation has been\n completed, the states that fall below the separatrix would end up in no\n infection, and the states above would end up in infection.</p>", "links"=>[], "tags"=>["probability", "inoculation", "temporal"], "article_id"=>565862, "categories"=>["Immunology", "Computational Biology", "Mathematics", "Medicine"], "users"=>["Josep M. Pujol", "Joseph E. Eisenberg", "Charles N. Haas", "James S. Koopman"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000399.g002", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_State_probability_distribution_at_the_end_of_inoculation_for_a_dose_of_and_temporal_exposure_length_of_0_1_h_B_1_0_h_C_10_0_h_and_D_50_0_h_/565862", "title"=>"State probability distribution at the end of inoculation () for a dose of and temporal exposure length of ) 0.1 h, B) 1.0 h, C) 10.0 h and D) 50.0 h.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 05:42:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/895929"], "description"=>"<p>The top graph comes from simulations using the parameter set defined in\n <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000399#pcbi-1000399-g005\" target=\"_blank\">Figure 5</a>. The\n bottom graph comes simulations using the parameter set .</p>", "links"=>[], "tags"=>["varying", "times", "inoculated"], "article_id"=>566388, "categories"=>["Immunology", "Computational Biology", "Mathematics", "Medicine"], "users"=>["Josep M. Pujol", "Joseph E. Eisenberg", "Charles N. Haas", "James S. Koopman"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000399.g008", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicted_effects_of_varying_exposure_times_when_inoculated_with_Cryptosporidium____parvum_/566388", "title"=>"Predicted effects of varying exposure times () when inoculated with <i>Cryptosporidium\n parvum</i>.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 05:45:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/895740"], "description"=>"<p>The estimated parameters are for the Exponential model, for the Beta-Poisson model [31] and for the Cumulative Dose model.</p>", "links"=>[], "tags"=>["curves", "exponential", "beta-poisson", "cumulative", "compared", "dataset", "rotavirus"], "article_id"=>566191, "categories"=>["Immunology", "Computational Biology", "Mathematics", "Medicine"], "users"=>["Josep M. Pujol", "Joseph E. Eisenberg", "Charles N. Haas", "James S. Koopman"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000399.g006", "stats"=>{"downloads"=>2, "page_views"=>21, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Dose_response_curves_based_on_the_Exponential_Model_the_Beta_Poisson_model_and_the_Cumulative_Dose_model_compared_to_the_experimental_dataset_for_Rotavirus____squares_/566191", "title"=>"Dose-response curves based on the Exponential Model (), the Beta-Poisson model () and the Cumulative Dose model () compared to the experimental dataset for Rotavirus\n (squares).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 05:44:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/895991"], "description"=>"<p>The main figure displays the probability of infection as function of the\n number of inoculation events. The line with circular markers comes from\n simulation results using the parameter set defined in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000399#pcbi-1000399-g005\" target=\"_blank\">Figure 5</a>, and the line\n with square markers comes from simulation results using the parameter\n set The insets below demonstrate three temporal patterns\n for three different patterns of inoculation events:\n A = 1,\n B = 4 and\n C = 50 events respectively. The solid\n line represents one instance of the 5000 replicas used in the\n experiment. The dashed line represents the average of dose inoculated\n over time.</p>", "links"=>[], "tags"=>["temporal", "patterns", "when", "inoculated"], "article_id"=>566446, "categories"=>["Immunology", "Computational Biology", "Mathematics", "Medicine"], "users"=>["Josep M. Pujol", "Joseph E. Eisenberg", "Charles N. Haas", "James S. Koopman"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000399.g009", "stats"=>{"downloads"=>2, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicted_effects_of_different_temporal_patterns_of_exposure_when____inoculated_with_Cryptosporidium_parvum_/566446", "title"=>"Predicted effects of different temporal patterns of exposure when\n inoculated with <i>Cryptosporidium parvum</i>.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 05:45:46"}
  • {"files"=>["https://ndownloader.figshare.com/files/895494"], "description"=>"<p>To avoid overlaps of the vectors they have been normalized. The solid red\n lines are the nullclines, the intersections of the nullclines are the\n fixed points (stable pathogen elimination equilibrium) and (unstable saddle point equilibrium). The dash black\n line is the separatrix that separates those configurations that will go\n to non-infection equilibrium, , and those that will diverge in the number of\n pathogens resulting on infection. The separatrix has been calculated\n numerically.</p>", "links"=>[], "tags"=>["deterministic", "cumulative", "a", "parameter"], "article_id"=>565948, "categories"=>["Immunology", "Computational Biology", "Mathematics", "Medicine"], "users"=>["Josep M. Pujol", "Joseph E. Eisenberg", "Charles N. Haas", "James S. Koopman"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000399.g003", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Vector_field_plot_of_the_deterministic_cumulative_dose_model_for_a____characteristic_parameter_set_/565948", "title"=>"Vector field plot of the deterministic cumulative dose model for a\n characteristic parameter set .", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 05:43:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/895642"], "description"=>"<p>The estimated parameters are for the Exponential model [30] and for the Cumulative Dose model.</p>", "links"=>[], "tags"=>["curves", "exponential", "cumulative", "compared", "dataset", "for"], "article_id"=>566092, "categories"=>["Immunology", "Computational Biology", "Mathematics", "Medicine"], "users"=>["Josep M. Pujol", "Joseph E. Eisenberg", "Charles N. Haas", "James S. Koopman"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000399.g005", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Dose_response_curves_based_on_the_Exponential_Model_and_the_Cumulative_Dose_model_compared_to_the_experimental_dataset_for_____Cryptosporidium_parvum_squares_/566092", "title"=>"Dose-response curves based on the Exponential Model () and the Cumulative Dose model () compared to the experimental dataset for\n <i>Cryptosporidium parvum</i> (squares).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 05:43:47"}
  • {"files"=>["https://ndownloader.figshare.com/files/896097"], "description"=>"<p>The estimated parameters are for the Exponential model [30]\n and for the Cumulative Dose model.</p>", "links"=>[], "tags"=>["for", "compared", "probability", "by", "exponential", "cumulative"], "article_id"=>566550, "categories"=>["Immunology", "Computational Biology", "Mathematics", "Medicine"], "users"=>["Josep M. Pujol", "Joseph E. Eisenberg", "Charles N. Haas", "James S. Koopman"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000399.t002", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Probability_of_infection_from_experimental_data_for_____Cryptosporidium_parvum_compared_to_the_probability_of_infection_predicted_by____the_Exponential_model_EM_and_the_Cumulative_Dose_CD_model_/566550", "title"=>"Probability of infection from experimental data for\n <i>Cryptosporidium parvum</i> () compared to the probability of infection predicted by\n the Exponential model (EM) and the Cumulative Dose (CD) model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-21 05:46:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/895840"], "description"=>"<p>Parameters are defined as stated in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000399#pcbi-1000399-g004\" target=\"_blank\">Figure 4</a>.</p>", "links"=>[], "tags"=>["varying", "times", "inoculated", "poliovirus"], "article_id"=>566291, "categories"=>["Immunology", "Computational Biology", "Mathematics", "Medicine"], "users"=>["Josep M. Pujol", "Joseph E. Eisenberg", "Charles N. Haas", "James S. Koopman"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000399.g007", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicted_effects_of_varying_exposure_times_when_inoculated_with_Poliovirus_type_1_/566291", "title"=>"Predicted effects of varying exposure times () when inoculated with Poliovirus type 1.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 05:44:56"}

PMC Usage Stats | Further Information

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Relative Metric

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