<HashMap><database>biostudies-literature</database><scores/><additional><submitter>van Bilsen JHM</submitter><funding>Stichting voor de Technische Wetenschappen</funding><funding>Ministerie van Economische Zaken</funding><funding>Dutch Research Council (NWO)</funding><pagination>206</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6480866</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>20(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>Oral immunotherapy (OIT) is a promising therapeutic approach to treat food allergic patients. However, concerns with regards to safety and long-term efficacy of OIT remain. There is a need to identify biomarkers that predict, monitor and/or evaluate the effects of OIT. Here we present a method to select candidate biomarkers for efficacy and safety assessment of OIT using the computational approaches Bayesian networks (BN) and Topological Data Analysis (TDA).&lt;h4>Results&lt;/h4>Data were used from fructo-oligosaccharide diet-supported OIT experiments performed in 3 independent cow's milk allergy (CMA) and 2 independent peanut allergy (PNA) experiments in mice. Bioinformatical approaches were used to understand the data structure. The BN predicted the efficacy of OIT in the CM</pubmed_abstract><journal>BMC bioinformatics</journal><pubmed_title>A network-based approach for identifying suitable biomarkers for oral immunotherapy of food allergy.</pubmed_title><pmcid>PMC6480866</pmcid><funding_grant_id>Not applicable</funding_grant_id><funding_grant_id>12652</funding_grant_id><pubmed_authors>Pieters RHH</pubmed_authors><pubmed_authors>Wagenaar L</pubmed_authors><pubmed_authors>Verschuren L</pubmed_authors><pubmed_authors>Knippels LMJ</pubmed_authors><pubmed_authors>van den Broek TJ</pubmed_authors><pubmed_authors>Smit JJ</pubmed_authors><pubmed_authors>Vonk MM</pubmed_authors><pubmed_authors>van Bilsen JHM</pubmed_authors><pubmed_authors>van Esch BCAM</pubmed_authors><pubmed_authors>Garssen J</pubmed_authors></additional><is_claimable>false</is_claimable><name>A network-based approach for identifying suitable biomarkers for oral immunotherapy of food allergy.</name><description>&lt;h4>Background&lt;/h4>Oral immunotherapy (OIT) is a promising therapeutic approach to treat food allergic patients. However, concerns with regards to safety and long-term efficacy of OIT remain. There is a need to identify biomarkers that predict, monitor and/or evaluate the effects of OIT. Here we present a method to select candidate biomarkers for efficacy and safety assessment of OIT using the computational approaches Bayesian networks (BN) and Topological Data Analysis (TDA).&lt;h4>Results&lt;/h4>Data were used from fructo-oligosaccharide diet-supported OIT experiments performed in 3 independent cow's milk allergy (CMA) and 2 independent peanut allergy (PNA) experiments in mice. Bioinformatical approaches were used to understand the data structure. The BN predicted the efficacy of OIT in the CM</description><dates><release>2019-01-01T00:00:00Z</release><publication>2019 Apr</publication><modification>2026-07-12T03:23:42.089Z</modification><creation>2019-06-06T22:48:39Z</creation></dates><accession>S-EPMC6480866</accession><cross_references><pubmed>31014233</pubmed><doi>10.1186/s12859-019-2802-9</doi></cross_references></HashMap>