{"id":157609,"date":"2008-12-01T00:00:00","date_gmt":"2008-12-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/immune-system-modeling-with-infer-net\/"},"modified":"2018-10-16T19:57:29","modified_gmt":"2018-10-17T02:57:29","slug":"immune-system-modeling-with-infer-net","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/immune-system-modeling-with-infer-net\/","title":{"rendered":"Immune System Modeling with Infer.NET"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Graphical models allow scientific prior knowledge to be incorporated into the statistical analysis of data, whilst also providing a vivid way to represent and communicate this knowledge. In this paper we develop a graphical model of the immune system as a means of analyzing immunological data from the Manchester Asthma and Allergy Study (MAAS). The analysis is achieved using the Infer.NET tool which allows Bayesian inference to be applied automatically to a specified graphical model.<\/p>\n<p>Our immune system model consists firstly of a Hidden Markov Model representing how allergen-specific skin prick tests (SPTs) and serum-specific IgE tests (SITs) change over time. By introducing a latent multinomial variable, we also cluster the children in an unsupervised manner into different sensitization classes. For 2 sensitization classes, the children who are vulnerable to allergies and have a high probability of having asthma (22%) are identified. For 5 sensitization classes, children in the first cluster, those who are vulnerable to allergies, have an even higher probability of having asthma (42%). The second part of the model involves using the inferred sensitization class as a label and 8 exposure variables in a Bayes Point Machine. Using multiple permutation tests, we conclude that the level of endotoxins and gender have a significant effect on a child\u2019s vulnerability to allergies.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Graphical models allow scientific prior knowledge to be incorporated into the statistical analysis of data, whilst also providing a vivid way to represent and communicate this knowledge. In this paper we develop a graphical model of the immune system as a means of analyzing immunological data from the Manchester Asthma and Allergy Study (MAAS). The [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13553],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-157609","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-medical-health-genomics","msr-locale-en_us"],"msr_publishername":"","msr_edition":"IEEE International Conference on e-Science (e-Science 2008),","msr_affiliation":"","msr_published_date":"2008-12-01","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"207972","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"escience_2page.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/escience_2page.pdf","id":207972,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":207972,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/escience_2page.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"jwinn","user_id":32457,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=jwinn"},{"type":"text","value":"Angela Simpson","user_id":0,"rest_url":false},{"type":"text","value":"Adnan Custovic","user_id":0,"rest_url":false},{"type":"text","value":"Vincent Y. 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