[{"publisher":"National Academy of Sciences","department":[{"_id":"MaJö"},{"_id":"HeEd"}],"quality_controlled":"1","publication":"PNAS","intvolume":"       110","status":"public","page":"E1695 - E1704","month":"04","date_created":"2018-12-11T11:59:47Z","pmid":1,"language":[{"iso":"eng"}],"doi":"10.1073/pnas.1304354110","citation":{"short":"C. Topp, A. Iyer Pascuzzi, J. Anderson, C. Lee, P. Zurek, O. Symonova, Y. Zheng, A. Bucksch, Y. Mileyko, T. Galkovskyi, B. Moore, J. Harer, H. Edelsbrunner, T. Mitchell Olds, J. Weitz, P. Benfey, PNAS 110 (2013) E1695–E1704.","ama":"Topp C, Iyer Pascuzzi A, Anderson J, et al. 3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture. <i>PNAS</i>. 2013;110(18):E1695-E1704. doi:<a href=\"https://doi.org/10.1073/pnas.1304354110\">10.1073/pnas.1304354110</a>","apa":"Topp, C., Iyer Pascuzzi, A., Anderson, J., Lee, C., Zurek, P., Symonova, O., … Benfey, P. (2013). 3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture. <i>PNAS</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.1304354110\">https://doi.org/10.1073/pnas.1304354110</a>","chicago":"Topp, Christopher, Anjali Iyer Pascuzzi, Jill Anderson, Cheng Lee, Paul Zurek, Olga Symonova, Ying Zheng, et al. “3D Phenotyping and Quantitative Trait Locus Mapping Identify Core Regions of the Rice Genome Controlling Root Architecture.” <i>PNAS</i>. National Academy of Sciences, 2013. <a href=\"https://doi.org/10.1073/pnas.1304354110\">https://doi.org/10.1073/pnas.1304354110</a>.","ista":"Topp C, Iyer Pascuzzi A, Anderson J, Lee C, Zurek P, Symonova O, Zheng Y, Bucksch A, Mileyko Y, Galkovskyi T, Moore B, Harer J, Edelsbrunner H, Mitchell Olds T, Weitz J, Benfey P. 2013. 3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture. PNAS. 110(18), E1695–E1704.","ieee":"C. Topp <i>et al.</i>, “3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture,” <i>PNAS</i>, vol. 110, no. 18. National Academy of Sciences, pp. E1695–E1704, 2013.","mla":"Topp, Christopher, et al. “3D Phenotyping and Quantitative Trait Locus Mapping Identify Core Regions of the Rice Genome Controlling Root Architecture.” <i>PNAS</i>, vol. 110, no. 18, National Academy of Sciences, 2013, pp. E1695–704, doi:<a href=\"https://doi.org/10.1073/pnas.1304354110\">10.1073/pnas.1304354110</a>."},"title":"3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture","day":"30","author":[{"full_name":"Topp, Christopher","first_name":"Christopher","last_name":"Topp"},{"last_name":"Iyer Pascuzzi","full_name":"Iyer Pascuzzi, Anjali","first_name":"Anjali"},{"first_name":"Jill","full_name":"Anderson, Jill","last_name":"Anderson"},{"first_name":"Cheng","full_name":"Lee, Cheng","last_name":"Lee"},{"full_name":"Zurek, Paul","first_name":"Paul","last_name":"Zurek"},{"last_name":"Symonova","first_name":"Olga","full_name":"Symonova, Olga","id":"3C0C7BC6-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Zheng","full_name":"Zheng, Ying","first_name":"Ying"},{"last_name":"Bucksch","first_name":"Alexander","full_name":"Bucksch, Alexander"},{"last_name":"Mileyko","first_name":"Yuriy","full_name":"Mileyko, Yuriy"},{"last_name":"Galkovskyi","full_name":"Galkovskyi, Taras","first_name":"Taras"},{"full_name":"Moore, Brad","first_name":"Brad","last_name":"Moore"},{"full_name":"Harer, John","first_name":"John","last_name":"Harer"},{"id":"3FB178DA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-9823-6833","full_name":"Edelsbrunner, Herbert","first_name":"Herbert","last_name":"Edelsbrunner"},{"first_name":"Thomas","full_name":"Mitchell Olds, Thomas","last_name":"Mitchell Olds"},{"first_name":"Joshua","full_name":"Weitz, Joshua","last_name":"Weitz"},{"first_name":"Philip","full_name":"Benfey, Philip","last_name":"Benfey"}],"type":"journal_article","publication_status":"published","main_file_link":[{"url":"http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4378147/","open_access":"1"}],"oa":1,"volume":110,"issue":"18","date_published":"2013-04-30T00:00:00Z","_id":"2822","abstract":[{"lang":"eng","text":"Identification of genes that control root system architecture in crop plants requires innovations that enable high-throughput and accurate measurements of root system architecture through time. We demonstrate the ability of a semiautomated 3D in vivo imaging and digital phenotyping pipeline to interrogate the quantitative genetic basis of root system growth in a rice biparental mapping population, Bala x Azucena. We phenotyped &gt;1,400 3D root models and &gt;57,000 2D images for a suite of 25 traits that quantified the distribution, shape, extent of exploration, and the intrinsic size of root networks at days 12, 14, and 16 of growth in a gellan gum medium. From these data we identified 89 quantitative trait loci, some of which correspond to those found previously in soil-grown plants, and provide evidence for genetic tradeoffs in root growth allocations, such as between the extent and thoroughness of exploration. We also developed a multivariate method for generating and mapping central root architecture phenotypes and used it to identify five major quantitative trait loci (r2 = 24-37%), two of which were not identified by our univariate analysis. Our imaging and analytical platform provides a means to identify genes with high potential for improving root traits and agronomic qualities of crops."}],"date_updated":"2021-01-12T06:59:58Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","external_id":{"pmid":["25673779"]},"scopus_import":1,"publist_id":"3979","year":"2013","oa_version":"Submitted Version"},{"title":"The adaptive topology of a digital image","conference":{"start_date":"2012-06-27","end_date":"2012-06-29","name":"ISVD: International Symposium on Voronoi Diagrams in Science and Engineering","location":"New Brunswick, NJ, USA "},"citation":{"ista":"Edelsbrunner H, Symonova O. 2012. The adaptive topology of a digital image. ISVD: International Symposium on Voronoi Diagrams in Science and Engineering, 41–48.","ieee":"H. Edelsbrunner and O. Symonova, “The adaptive topology of a digital image,” presented at the ISVD: International Symposium on Voronoi Diagrams in Science and Engineering, New Brunswick, NJ, USA , 2012, pp. 41–48.","chicago":"Edelsbrunner, Herbert, and Olga Symonova. “The Adaptive Topology of a Digital Image,” 41–48. IEEE, 2012. <a href=\"https://doi.org/10.1109/ISVD.2012.11\">https://doi.org/10.1109/ISVD.2012.11</a>.","mla":"Edelsbrunner, Herbert, and Olga Symonova. <i>The Adaptive Topology of a Digital Image</i>. IEEE, 2012, pp. 41–48, doi:<a href=\"https://doi.org/10.1109/ISVD.2012.11\">10.1109/ISVD.2012.11</a>.","short":"H. Edelsbrunner, O. Symonova, in:, IEEE, 2012, pp. 41–48.","apa":"Edelsbrunner, H., &#38; Symonova, O. (2012). The adaptive topology of a digital image (pp. 41–48). Presented at the ISVD: International Symposium on Voronoi Diagrams in Science and Engineering, New Brunswick, NJ, USA : IEEE. <a href=\"https://doi.org/10.1109/ISVD.2012.11\">https://doi.org/10.1109/ISVD.2012.11</a>","ama":"Edelsbrunner H, Symonova O. The adaptive topology of a digital image. In: IEEE; 2012:41-48. doi:<a href=\"https://doi.org/10.1109/ISVD.2012.11\">10.1109/ISVD.2012.11</a>"},"type":"conference","author":[{"id":"3FB178DA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-9823-6833","first_name":"Herbert","full_name":"Edelsbrunner, Herbert","last_name":"Edelsbrunner"},{"full_name":"Symonova, Olga","first_name":"Olga","last_name":"Symonova","id":"3C0C7BC6-F248-11E8-B48F-1D18A9856A87"}],"day":"06","doi":"10.1109/ISVD.2012.11","ddc":["000"],"language":[{"iso":"eng"}],"page":"41 - 48","date_created":"2018-12-11T12:00:15Z","month":"08","publisher":"IEEE","status":"public","quality_controlled":"1","department":[{"_id":"HeEd"},{"_id":"MaJö"}],"has_accepted_license":"1","oa_version":"Submitted Version","year":"2012","publist_id":"3844","scopus_import":1,"date_updated":"2021-01-12T07:00:35Z","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"2903","date_published":"2012-08-06T00:00:00Z","abstract":[{"lang":"eng","text":"In order to enjoy a digital version of the Jordan Curve Theorem, it is common to use the closed topology for the foreground and the open topology for the background of a 2-dimensional binary image. In this paper, we introduce a single topology that enjoys this theorem for all thresholds decomposing a real-valued image into foreground and background. This topology is easy to construct and it generalizes to n-dimensional images."}],"file":[{"date_created":"2018-12-12T10:09:41Z","content_type":"application/pdf","file_id":"4765","relation":"main_file","date_updated":"2020-07-14T12:45:52Z","access_level":"open_access","checksum":"444869a4e8abf07834f88b6e5cb5e9c3","file_name":"IST-2016-545-v1+1_2012-P-10-AdaptiveTopology.pdf","file_size":760548,"creator":"system"}],"oa":1,"publication_status":"published","pubrep_id":"545","file_date_updated":"2020-07-14T12:45:52Z"}]