\u00c9ric Audemard<\/strong>,\u00a0How to improve biomarkers selection using predictive genes<\/p>\nThe accurate detection of predictive genes biomarker from high throughput technologies such as RNA sequencing has become an important, yet challenging task. Currently, most of the available methods are based on statistical tests to select Differentially Expressed Genes (DEG). However, to maximize the probability of success and to limit time and resource-consuming validations, candidate genes need to be selected based on criteria in line with the final objective, which is their predictive capabilities. To rank best Predictive Genes (PG) we develop EPCY, a method based on servals classifiers trained by cross-validation. Using both bulk (Leucegene dataset) and single-cell (10X dataset) RNA sequencing data, we demonstrated how this method allows the selection of the best candidates compared to benchmark DEG analysis-based methods. More specifically, we demonstrated the stability of EPCY analysis when the number of cases composing the dataset varies.<\/p>\n
Nadia Tahiri<\/strong>, Quantitative Structure-Activity Relationship (QSAR) Modeling to Predict the Transfer of Environmental Chemicals across the Placenta<\/p>\nThe increasing diversity of environmental chemicals in the environment, some of which may be developmental toxicants, is a public health concern. The aim of this work was to contribute to the development of rapid and effective methods to assess prenatal exposure. Quantitative structure-activity relationships (QSAR) modeling has emerged as a promising method in the development of a predictive model for the placental transfer of contaminants. Fetal to maternal plasma or serum concentration ratios for 105 chemicals were extracted from the literature, and 214 molecular descriptors were generated for each of these chemicals. Ten predictive models were built using Molecular Operating Environment (MOE) software, and the Python and R programming languages. Training and test datasets were used, respectively, to build and validate the models. The Applicability Domain Tool v1.0 was used to determine the applicability domain. The models developed with the partial least squares regression method in MOE and SuperLearner in R, showed the best precision and predictivity, with internal coefficients of determination (R2) of 0.88 and 0.82, cross-validated R2s of 0.72 and 0.57, and external R2s of 0.73 and 0.74, respectively. The inclusion of all test chemicals by the domain of applicability demonstrated the reliability and relevance of the model predictions. The results obtained demonstrate that QSAR modeling can help quantify the placental transfer of environmental chemicals.<\/p>\n","protected":false},"excerpt":{"rendered":"
Joignez-vous \u00e0 nous virtuellement, mercredi le 9 juin \u00e0 16h30 pour en apprendre davantage sur deux sujets bioinfo tr\u00e8s int\u00e9ressants. Vous aurez le plaisir d\u2019entendre : \u00c9ric Audemard,\u00a0How to improve biomarkers selection using predictive genes Nadia Tahiri, Quantitative Structure-Activity Relationship (QSAR) Modeling to Predict the Transfer of Environmental Chemicals across the Placenta \u00c9ric Audemard a […]<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[],"class_list":{"0":"post-2092","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-page-accueil"},"_links":{"self":[{"href":"https:\/\/monbug.ca\/fr\/wp-json\/wp\/v2\/posts\/2092","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/monbug.ca\/fr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/monbug.ca\/fr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/monbug.ca\/fr\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/monbug.ca\/fr\/wp-json\/wp\/v2\/comments?post=2092"}],"version-history":[{"count":7,"href":"https:\/\/monbug.ca\/fr\/wp-json\/wp\/v2\/posts\/2092\/revisions"}],"predecessor-version":[{"id":2109,"href":"https:\/\/monbug.ca\/fr\/wp-json\/wp\/v2\/posts\/2092\/revisions\/2109"}],"wp:attachment":[{"href":"https:\/\/monbug.ca\/fr\/wp-json\/wp\/v2\/media?parent=2092"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/monbug.ca\/fr\/wp-json\/wp\/v2\/categories?post=2092"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/monbug.ca\/fr\/wp-json\/wp\/v2\/tags?post=2092"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}