{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T10:15:26Z","timestamp":1760955326306},"reference-count":26,"publisher":"Hindawi Limited","license":[{"start":{"date-parts":[[2011,9,27]],"date-time":"2011-09-27T00:00:00Z","timestamp":1317081600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Advances in Bioinformatics"],"published-print":{"date-parts":[[2011,9,27]]},"abstract":"<jats:p>Identifying the various gene expression response patterns is a challenging issue in expression microarray time-course experiments. Due to heterogeneity in the regulatory reaction among thousands of genes tested, it is impossible to manually characterize a parametric form for each of the time-course pattern in a gene by gene manner. We introduce a growth curve model with fractional polynomials to automatically capture the various time-dependent expression patterns and meanwhile efficiently handle missing values due to incomplete observations. For each gene, our procedure compares the performances among fractional polynomial models with power terms from a set of fixed values that offer a wide range of curve shapes and suggests a best fitting model. After a limited simulation study, the model has been applied to our human <jats:italic>in vivo<\/jats:italic> irritated epidermis data with missing observations to investigate time-dependent transcriptional responses to a chemical irritant. Our method was able to identify the various nonlinear time-course expression trajectories. The integration of growth curves with fractional polynomials provides a flexible way to model different time-course patterns together with model selection and significant gene identification strategies that can be applied in microarray-based time-course gene expression experiments with missing observations.<\/jats:p>","DOI":"10.1155\/2011\/261514","type":"journal-article","created":{"date-parts":[[2011,9,28]],"date-time":"2011-09-28T03:06:40Z","timestamp":1317179200000},"page":"1-6","source":"Crossref","is-referenced-by-count":4,"title":["A Growth Curve Model with Fractional Polynomials for Analysing Incomplete Time-Course Data in Microarray Gene Expression Studies"],"prefix":"10.1155","volume":"2011","author":[{"given":"Qihua","family":"Tan","sequence":"first","affiliation":[{"name":"Department of Clinical Genetics, Odense University Hospital, Sdr. Boulevard 29, 5000 Odense C, Denmark"},{"name":"Epidemiology and Department of Biostatistics, Institute of Public Health, University of Southern Denmark, J. B. Winsl\u00f8ws Vej 9B, 5000 Odense C, Denmark"}]},{"given":"Mads","family":"Thomassen","sequence":"additional","affiliation":[{"name":"Department of Clinical Genetics, Odense University Hospital, Sdr. Boulevard 29, 5000 Odense C, Denmark"}]},{"given":"Jacob v. B.","family":"Hjelmborg","sequence":"additional","affiliation":[{"name":"Epidemiology and Department of Biostatistics, Institute of Public Health, University of Southern Denmark, J. B. Winsl\u00f8ws Vej 9B, 5000 Odense C, Denmark"}]},{"given":"Anders","family":"Clemmensen","sequence":"additional","affiliation":[{"name":"Department of Dermatology and Allergy Center, Odense University Hospital, Sdr. 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