{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T03:36:48Z","timestamp":1773805008100,"version":"3.50.1"},"reference-count":19,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2021,11,24]],"date-time":"2021-11-24T00:00:00Z","timestamp":1637712000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Genet."],"abstract":"<jats:p>Gene expression is controlled by multiple regulators and their interactions. Data from genome-wide gene expression assays can be used to estimate molecular activities of regulators within a model organism and extrapolate them to biological processes in humans. This approach is valuable in studies to better understand complex human biological systems which may be involved in diseases and hence, have potential clinical relevance. In order to achieve this, it is necessary to infer gene interactions that are not directly observed (i.e. latent or hidden) by way of structural equation modeling (SEM) on the expression levels or activities of the downstream targets of regulator genes. Here we developed an R Shiny application, termed \u201cStructural Equation Modeling of In silico Perturbations (SEMIPs)\u201d to compute a two-sided t-statistic (T-score) from analysis of gene expression data, as a surrogate to gene activity in a given human specimen. SEMIPs can be used in either correlational studies between outcome variables of interest or subsequent model fitting on multiple variables. This application implements a 3-node SEM model that consists of two upstream regulators as input variables and one downstream reporter as an outcome variable to examine the significance of interactions among these variables. SEMIPs enables scientists to investigate gene interactions among three variables through computational and mathematical modeling (i.e. <jats:italic>in silico<\/jats:italic>). In a case study using SEMIPs, we have shown that putative direct downstream genes of the GATA Binding Protein 2 (GATA2) transcription factor are sufficient to infer its activities <jats:italic>in silico<\/jats:italic> for the conserved progesterone receptor (PGR)-GATA2-SRY-box transcription factor 17 (SOX17) genetic network in the human uterine endometrium.<\/jats:p>","DOI":"10.3389\/fgene.2021.727532","type":"journal-article","created":{"date-parts":[[2021,11,30]],"date-time":"2021-11-30T22:17:26Z","timestamp":1638310646000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Structural Equation Modeling of In silico Perturbations"],"prefix":"10.3389","volume":"12","author":[{"given":"Jianying","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pierre R.","family":"Bushel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lin","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kevin","family":"Day","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianyuan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesco J.","family":"DeMayo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"San-Pin","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian-Liang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2021,11,24]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"4078","DOI":"10.1200\/jco.2007.13.4429","article-title":"Insulin-like Growth Factor-I Activates Gene Transcription Programs Strongly Associated with Poor Breast Cancer Prognosis","volume":"26","author":"Creighton","year":"2008","journal-title":"J. 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A Multidisciplinary J."},{"key":"B7","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1037\/1082-989x.3.4.424","article-title":"Fit Indices in Covariance Structure Modeling: Sensitivity to Underparameterized Model Misspecification","volume":"3","author":"Hu","year":"1998","journal-title":"Psychol. Methods"},{"key":"B8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/10705519909540118","article-title":"Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria versus New Alternatives","volume":"6","author":"Hu","year":"1999","journal-title":"Struct. Equ. Model. A Multidisciplinary J."},{"key":"B9","doi-asserted-by":"publisher","first-page":"19411","DOI":"10.1038\/srep19411","article-title":"An Endometrial Gene Expression Signature Accurately Predicts Recurrent Implantation Failure after IVF","volume":"6","author":"Koot","year":"2016","journal-title":"Sci. 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