{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["van Bilsen JHM"],"funding":["Stichting voor de Technische Wetenschappen","Ministerie van Economische Zaken","Dutch Research Council (NWO)"],"pagination":["206"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC6480866"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["20(1)"],"pubmed_abstract":["<h4>Background</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).<h4>Results</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"],"journal":["BMC bioinformatics"],"pubmed_title":["A network-based approach for identifying suitable biomarkers for oral immunotherapy of food allergy."],"pmcid":["PMC6480866"],"funding_grant_id":["Not applicable","12652"],"pubmed_authors":["Pieters RHH","Wagenaar L","Verschuren L","Knippels LMJ","van den Broek TJ","Smit JJ","Vonk MM","van Bilsen JHM","van Esch BCAM","Garssen J"],"additional_accession":[]},"is_claimable":false,"name":"A network-based approach for identifying suitable biomarkers for oral immunotherapy of food allergy.","description":"<h4>Background</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).<h4>Results</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","dates":{"release":"2019-01-01T00:00:00Z","publication":"2019 Apr","modification":"2026-07-12T03:23:42.089Z","creation":"2019-06-06T22:48:39Z"},"accession":"S-EPMC6480866","cross_references":{"pubmed":["31014233"],"doi":["10.1186/s12859-019-2802-9"]}}