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Báo cáo y học: "ranscription Network Project, Institute for Data Analysis and Visualization, University of California, Davis"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Minireview cung cấp cho các bạn kiến thức về ngành y đề tài: Transcription Network Project, Institute for Data Analysis and Visualization, University of California, Davis. | Open Access Three-dimensional morphology and gene expression in the Drosophila blastoderm at cellular resolution I data acquisition pipeline Cris L Luengo Hendriks Soile VE Keranen Charless C Fowlkes Lisa Simirenko Gunther H Weber Angela H DePace Clara Henriquez David W Kaszuba Bernd Hamann Michael B Eisen Jitendra Malik Damir Sudar Mark D Biggin and David W Knowles Addresses Berkeley Drosophila Transcription Network Project Life Sciences Division Lawrence Berkeley National Laboratory One Cyclotron Road Berkeley CA 94720 USA. Berkeley Drosophila Transcription Network Project Genomics Division Lawrence Berkeley National Laboratory One Cyclotron Road Berkeley CA 94720 USA. Berkeley Drosophila Transcription Network Project Department of Electrical Engineering and Computer Science University of California Berkeley CA 94720 USA. Berkeley Drosophila Transcription Network Project Institute for Data Analysis and Visualization University of California Davis CA 95616 USA. H These authors contributed equally to this work. Correspondence David W Knowles. Email DWKnowles@lbl.gov Published 21 December 2006 Genome Biology 2006 7 R123 doi 10.1186 gb-2006-7- 12-r 123 The electronic version of this article is the complete one and can be found online at http genomebiology.com 2006 7 12 R123 Received 1 August 2006 Revised 17 November 2006 Accepted 21 December 2006 2006 Luengo Hendriks et al. licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License http creativecommons.org licenses by 2.0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background To model and thoroughly understand animal transcription networks it is essential to derive accurate spatial and temporal descriptions of developing gene expression patterns with cellular resolution. Results Here we describe a suite of methods that provide the first quantitative .