{"id":2944,"date":"2019-06-02T21:11:59","date_gmt":"2019-06-02T21:11:59","guid":{"rendered":"https:\/\/clinomic.ai\/?p=2944"},"modified":"2023-10-05T14:37:45","modified_gmt":"2023-10-05T14:37:45","slug":"new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models","status":"publish","type":"post","link":"https:\/\/www.clinomic.ai\/ro\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/","title":{"rendered":"New approach in Likelihood-Based Adaptive Learning for Stochastic State-Based Models"},"content":{"rendered":"\n<div class=\"wp-block-image\"><figure class=\"aligncenter\"><img decoding=\"async\" src=\"https:\/\/clinomic.ai\/wp-content\/uploads\/2019\/06\/art-board-game-challenge-163064-1024x683.jpg\" alt=\"\" class=\"wp-image-2945\"\/><\/figure><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">SSMs are a useful modelling tool in systems biology and medicine. While models in these disciplines are traditionally hand-crafted, an automated generation based on experimental data becomes a topic of research interest. In particular, our goal was to classify measured processes using the generated models. An innovative likelihood-based adaptive learning approach capable of learning the structural parameters, i.e., the arc weights of SSMs from data and exploiting the reliability of detected inputs. Its convergence behavior is analyzed and an expression for the error at steady state is derived. Simulations assess the performance of the proposed and existing algorithms for a gene regulatory network.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Read our newest publication together with our partner universities <a href=\"https:\/\/ieeexplore.ieee.org\/document\/8717701\">here, Full text can be requested via our contact form.<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>SSMs are a useful modelling tool in systems biology and medicine. While models in these disciplines are traditionally hand-crafted, an automated generation based on experimental data becomes a topic of research interest. In particular, our goal was to classify measured processes using the generated models. An innovative likelihood-based adaptive learning approach capable of learning the [&#8230;]<\/p>\n<p><a class=\"btn btn-secondary understrap-read-more-link\" href=\"https:\/\/www.clinomic.ai\/ro\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/\">Read More&#8230;<\/a><\/p>\n","protected":false},"author":4,"featured_media":3074,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"iawp_total_views":12,"footnotes":""},"categories":[10],"tags":[256],"class_list":["post-2944","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-publications","tag-ailab"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>New approach in Likelihood-Based Adaptive Learning for Stochastic State-Based Models - Clinomic<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/\" \/>\n<meta property=\"og:locale\" content=\"ro_RO\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"New approach in Likelihood-Based Adaptive Learning for Stochastic State-Based Models - Clinomic\" \/>\n<meta property=\"og:description\" content=\"SSMs are a useful modelling tool in systems biology and medicine. While models in these disciplines are traditionally hand-crafted, an automated generation based on experimental data becomes a topic of research interest. In particular, our goal was to classify measured processes using the generated models. An innovative likelihood-based adaptive learning approach capable of learning the [...]Read More...\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/\" \/>\n<meta property=\"og:site_name\" content=\"Clinomic\" \/>\n<meta property=\"article:published_time\" content=\"2019-06-02T21:11:59+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-10-05T14:37:45+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.clinomic.ai\/wp-content\/uploads\/2019\/06\/Likelihood-Based-Adaptive-Learning-for-Stochastic-State-Based-Models.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1024\" \/>\n\t<meta property=\"og:image:height\" content=\"683\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Arne Peine\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Scris de\" \/>\n\t<meta name=\"twitter:data1\" content=\"Arne Peine\" \/>\n\t<meta name=\"twitter:label2\" content=\"Timp estimat pentru citire\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minut\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/2019\\\/06\\\/02\\\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/2019\\\/06\\\/02\\\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\\\/\"},\"author\":{\"name\":\"Arne Peine\",\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/#\\\/schema\\\/person\\\/96e364f58fe927a66f5cfbfe4064b257\"},\"headline\":\"New approach in Likelihood-Based Adaptive Learning for Stochastic State-Based Models\",\"datePublished\":\"2019-06-02T21:11:59+00:00\",\"dateModified\":\"2023-10-05T14:37:45+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/2019\\\/06\\\/02\\\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\\\/\"},\"wordCount\":133,\"image\":{\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/2019\\\/06\\\/02\\\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.clinomic.ai\\\/wp-content\\\/uploads\\\/2019\\\/06\\\/Likelihood-Based-Adaptive-Learning-for-Stochastic-State-Based-Models.jpg\",\"keywords\":[\"ailab\"],\"articleSection\":[\"Publications with partner universities\"],\"inLanguage\":\"ro-RO\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/2019\\\/06\\\/02\\\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\\\/\",\"url\":\"https:\\\/\\\/www.clinomic.ai\\\/2019\\\/06\\\/02\\\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\\\/\",\"name\":\"New approach in Likelihood-Based Adaptive Learning for Stochastic State-Based Models - Clinomic\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/2019\\\/06\\\/02\\\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/2019\\\/06\\\/02\\\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.clinomic.ai\\\/wp-content\\\/uploads\\\/2019\\\/06\\\/Likelihood-Based-Adaptive-Learning-for-Stochastic-State-Based-Models.jpg\",\"datePublished\":\"2019-06-02T21:11:59+00:00\",\"dateModified\":\"2023-10-05T14:37:45+00:00\",\"author\":{\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/#\\\/schema\\\/person\\\/96e364f58fe927a66f5cfbfe4064b257\"},\"breadcrumb\":{\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/2019\\\/06\\\/02\\\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\\\/#breadcrumb\"},\"inLanguage\":\"ro-RO\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/www.clinomic.ai\\\/2019\\\/06\\\/02\\\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"ro-RO\",\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/2019\\\/06\\\/02\\\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\\\/#primaryimage\",\"url\":\"https:\\\/\\\/www.clinomic.ai\\\/wp-content\\\/uploads\\\/2019\\\/06\\\/Likelihood-Based-Adaptive-Learning-for-Stochastic-State-Based-Models.jpg\",\"contentUrl\":\"https:\\\/\\\/www.clinomic.ai\\\/wp-content\\\/uploads\\\/2019\\\/06\\\/Likelihood-Based-Adaptive-Learning-for-Stochastic-State-Based-Models.jpg\",\"width\":1024,\"height\":683,\"caption\":\"Likelihood-Based Adaptive Learning for Stochastic State-Based Models\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/2019\\\/06\\\/02\\\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Startseite\",\"item\":\"https:\\\/\\\/www.clinomic.ai\\\/ro\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"New approach in Likelihood-Based Adaptive Learning for Stochastic State-Based Models\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/#website\",\"url\":\"https:\\\/\\\/www.clinomic.ai\\\/\",\"name\":\"Clinomic\",\"description\":\"Rethinking Critical Care\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/www.clinomic.ai\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"ro-RO\"},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/www.clinomic.ai\\\/#\\\/schema\\\/person\\\/96e364f58fe927a66f5cfbfe4064b257\",\"name\":\"Arne Peine\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"ro-RO\",\"@id\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/?s=96&d=mm&r=g\",\"url\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/?s=96&d=mm&r=g\",\"contentUrl\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/?s=96&d=mm&r=g\",\"caption\":\"Arne Peine\"},\"url\":\"#\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"New approach in Likelihood-Based Adaptive Learning for Stochastic State-Based Models - Clinomic","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/","og_locale":"ro_RO","og_type":"article","og_title":"New approach in Likelihood-Based Adaptive Learning for Stochastic State-Based Models - Clinomic","og_description":"SSMs are a useful modelling tool in systems biology and medicine. While models in these disciplines are traditionally hand-crafted, an automated generation based on experimental data becomes a topic of research interest. In particular, our goal was to classify measured processes using the generated models. An innovative likelihood-based adaptive learning approach capable of learning the [...]Read More...","og_url":"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/","og_site_name":"Clinomic","article_published_time":"2019-06-02T21:11:59+00:00","article_modified_time":"2023-10-05T14:37:45+00:00","og_image":[{"width":1024,"height":683,"url":"https:\/\/www.clinomic.ai\/wp-content\/uploads\/2019\/06\/Likelihood-Based-Adaptive-Learning-for-Stochastic-State-Based-Models.jpg","type":"image\/jpeg"}],"author":"Arne Peine","twitter_card":"summary_large_image","twitter_misc":{"Scris de":"Arne Peine","Timp estimat pentru citire":"1 minut"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/#article","isPartOf":{"@id":"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/"},"author":{"name":"Arne Peine","@id":"https:\/\/www.clinomic.ai\/#\/schema\/person\/96e364f58fe927a66f5cfbfe4064b257"},"headline":"New approach in Likelihood-Based Adaptive Learning for Stochastic State-Based Models","datePublished":"2019-06-02T21:11:59+00:00","dateModified":"2023-10-05T14:37:45+00:00","mainEntityOfPage":{"@id":"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/"},"wordCount":133,"image":{"@id":"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/#primaryimage"},"thumbnailUrl":"https:\/\/www.clinomic.ai\/wp-content\/uploads\/2019\/06\/Likelihood-Based-Adaptive-Learning-for-Stochastic-State-Based-Models.jpg","keywords":["ailab"],"articleSection":["Publications with partner universities"],"inLanguage":"ro-RO"},{"@type":"WebPage","@id":"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/","url":"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/","name":"New approach in Likelihood-Based Adaptive Learning for Stochastic State-Based Models - Clinomic","isPartOf":{"@id":"https:\/\/www.clinomic.ai\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/#primaryimage"},"image":{"@id":"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/#primaryimage"},"thumbnailUrl":"https:\/\/www.clinomic.ai\/wp-content\/uploads\/2019\/06\/Likelihood-Based-Adaptive-Learning-for-Stochastic-State-Based-Models.jpg","datePublished":"2019-06-02T21:11:59+00:00","dateModified":"2023-10-05T14:37:45+00:00","author":{"@id":"https:\/\/www.clinomic.ai\/#\/schema\/person\/96e364f58fe927a66f5cfbfe4064b257"},"breadcrumb":{"@id":"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/#breadcrumb"},"inLanguage":"ro-RO","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/"]}]},{"@type":"ImageObject","inLanguage":"ro-RO","@id":"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/#primaryimage","url":"https:\/\/www.clinomic.ai\/wp-content\/uploads\/2019\/06\/Likelihood-Based-Adaptive-Learning-for-Stochastic-State-Based-Models.jpg","contentUrl":"https:\/\/www.clinomic.ai\/wp-content\/uploads\/2019\/06\/Likelihood-Based-Adaptive-Learning-for-Stochastic-State-Based-Models.jpg","width":1024,"height":683,"caption":"Likelihood-Based Adaptive Learning for Stochastic State-Based Models"},{"@type":"BreadcrumbList","@id":"https:\/\/www.clinomic.ai\/2019\/06\/02\/new-approach-in-likelihood-based-adaptive-learning-for-stochastic-state-based-models\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Startseite","item":"https:\/\/www.clinomic.ai\/ro\/"},{"@type":"ListItem","position":2,"name":"New approach in Likelihood-Based Adaptive Learning for Stochastic State-Based Models"}]},{"@type":"WebSite","@id":"https:\/\/www.clinomic.ai\/#website","url":"https:\/\/www.clinomic.ai\/","name":"Clinomic","description":"Rethinking Critical Care","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.clinomic.ai\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"ro-RO"},{"@type":"Person","@id":"https:\/\/www.clinomic.ai\/#\/schema\/person\/96e364f58fe927a66f5cfbfe4064b257","name":"Arne Peine","image":{"@type":"ImageObject","inLanguage":"ro-RO","@id":"https:\/\/secure.gravatar.com\/avatar\/?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/?s=96&d=mm&r=g","caption":"Arne Peine"},"url":"#"}]}},"_links":{"self":[{"href":"https:\/\/www.clinomic.ai\/ro\/wp-json\/wp\/v2\/posts\/2944","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.clinomic.ai\/ro\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.clinomic.ai\/ro\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.clinomic.ai\/ro\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.clinomic.ai\/ro\/wp-json\/wp\/v2\/comments?post=2944"}],"version-history":[{"count":1,"href":"https:\/\/www.clinomic.ai\/ro\/wp-json\/wp\/v2\/posts\/2944\/revisions"}],"predecessor-version":[{"id":3076,"href":"https:\/\/www.clinomic.ai\/ro\/wp-json\/wp\/v2\/posts\/2944\/revisions\/3076"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.clinomic.ai\/ro\/wp-json\/wp\/v2\/media\/3074"}],"wp:attachment":[{"href":"https:\/\/www.clinomic.ai\/ro\/wp-json\/wp\/v2\/media?parent=2944"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.clinomic.ai\/ro\/wp-json\/wp\/v2\/categories?post=2944"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.clinomic.ai\/ro\/wp-json\/wp\/v2\/tags?post=2944"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}