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dc.creatorYuan, L
dc.creatorPan, C
dc.creatorJi, S
dc.creatorMcCutchan, M
dc.creatorZhou, ZH
dc.creatorNewfeld, SJ
dc.creatorKumar, S
dc.creatorYe, J
dc.date.accessioned2021-01-31T18:16:58Z
dc.date.available2021-01-31T18:16:58Z
dc.date.issued2014-01-01
dc.identifier.issn1367-4803
dc.identifier.issn1460-2059
dc.identifier.doihttp://dx.doi.org/10.34944/dspace/5336
dc.identifier.other24300439 (pubmed)
dc.identifier.urihttp://hdl.handle.net/20.500.12613/5354
dc.description.abstractMotivation: Drosophila melanogaster is a major model organism for investigating the function and interconnection of animal genes in the earliest stages of embryogenesis. Today, images capturing Drosophila gene expression patterns are being produced at a higher throughput than ever before. The analysis of spatial patterns of gene expression is most biologically meaningful when images from a similar time point during development are compared. Thus, the critical first step is to determine the developmental stage of an embryo. This information is also needed to observe and analyze expression changes over developmental time. Currently, developmental stages (time) of embryos in images capturing spatial expression pattern are annotated manually, which is time-and labor-intensive. Embryos are often designated into stage ranges, making the information on developmental time course. This makes downstream analyses inefficient and biological interpretations of similarities and differences in spatial expression patterns challenging, particularly when using automated tools for analyzing expression patterns of large number of images.Results: Here, we present a new computational approach to annotate developmental stage for Drosophila embryos in the gene expression images. In an analysis of 3724 images, the new approach shows high accuracy in predicting the developmental stage correctly (79%). In addition, it provides a stage score that enables one to more finely annotate each embryo so that they are divided into early and late periods of development within standard stage demarcations. Stage scores for all images containing expression patterns of the same gene enable a direct way to view expression changes over developmental time for any gene. We show that the genomewide-expression-maps generated using images from embryos in refined stages illuminate global gene activities and changes much better, and more refined stage annotations improve our ability to better interpret results when expression pattern matches are discovered between genes. © 2013 The Author.
dc.format.extent266-273
dc.language.isoen
dc.relation.haspartBioinformatics
dc.relation.isreferencedbyOxford University Press (OUP)
dc.rightsCC BY
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/
dc.subjectAlgorithms
dc.subjectAnimals
dc.subjectComputational Biology
dc.subjectDrosophila Proteins
dc.subjectDrosophila melanogaster
dc.subjectEmbryo, Nonmammalian
dc.subjectEmbryonic Development
dc.subjectGene Expression Profiling
dc.subjectGene Expression Regulation, Developmental
dc.subjectImage Processing, Computer-Assisted
dc.subjectPattern Recognition, Automated
dc.titleAutomated annotation of developmental stages of Drosophila embryos in images containing spatial patterns of expression
dc.typeArticle
dc.type.genreJournal Article
dc.relation.doi10.1093/bioinformatics/btt648
dc.ada.noteFor Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu
dc.creator.orcidKumar, Sudhir|0000-0002-9918-8212
dc.date.updated2021-01-31T18:16:55Z
refterms.dateFOA2021-01-31T18:16:59Z


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