{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,30]],"date-time":"2026-05-30T03:00:53Z","timestamp":1780110053744,"version":"3.54.0"},"reference-count":19,"publisher":"Oxford University Press (OUP)","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2007,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Gene expression patterns obtained by in situ mRNA hybridization provide important information about different genes during Drosophila embryogenesis. So far, annotations of these images are done by manually assigning a subset of anatomy ontology terms to an image. This time-consuming process depends heavily on the consistency of experts.<\/jats:p><jats:p>Results: We develop a system to automatically annotate a fruitfly's embryonic tissue in which a gene has expression. We formulate the task as an image pattern recognition problem. For a new fly embryo image, our system answers two questions: (1) Which stage range does an image belong to? (2) Which annotations should be assigned to an image? We propose to identify the wavelet embryo features by multi-resolution 2D wavelet discrete transform, followed by min-redundancy max-relevance feature selection, which yields optimal distinguishing features for an annotation. We then construct a series of parallel bi-class predictors to solve the multi-objective annotation problem since each image may correspond to multiple annotations.<\/jats:p><jats:p>Supplementary information: The complete annotation prediction results are available at: http:\/\/www.cs.niu.edu\/~jzhou\/papers\/fruitfly and http:\/\/research.janelia.org\/peng\/proj\/fly_embryo_annotation\/. The datasets used in experiments will be available upon request to the correspondence author.<\/jats:p><jats:p>Contact: \u00a0jzhou@cs.niu.edu and pengh@janelia.hhmi.org<\/jats:p>","DOI":"10.1093\/bioinformatics\/btl680","type":"journal-article","created":{"date-parts":[[2007,1,20]],"date-time":"2007-01-20T01:12:50Z","timestamp":1169255570000},"page":"589-596","source":"Crossref","is-referenced-by-count":51,"title":["Automatic recognition and annotation of gene expression patterns of fly embryos"],"prefix":"10.1093","volume":"23","author":[{"given":"Jie","family":"Zhou","sequence":"first","affiliation":[{"name":"1 Department of Computer Science, Northern Illinois University, DeKalb, IL 60115 and 2Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 200147, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanchuan","family":"Peng","sequence":"additional","affiliation":[{"name":"1 Department of Computer Science, Northern Illinois University, DeKalb, IL 60115 and 2Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 200147, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2007,1,22]]},"reference":[{"key":"2023041109375324000_","doi-asserted-by":"crossref","first-page":"e41","DOI":"10.1371\/journal.pcbi.0010041","article-title":"A digital atlas to characterize the mouse brain transcriptome","volume":"1","author":"Carson","year":"2005","journal-title":"PLoS Comput. 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