tailieunhanh - Báo cáo y học: "MouseCyc: a curated biochemical pathways database for the laboratory mouse"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Wertheim cung cấp cho các bạn kiến thức về ngành y đề tài: MouseCyc: a curated biochemical pathways database for the laboratory mouse. | Open Access Software MouseCyc a curated biochemical pathways database for the laboratory mouse Alexei V Evsikov Mary E Dolan Michael P Genrich Emily Patek and Carol J Bult Address The Jackson Laboratory Main Street Bar Harbor ME 04609 USA. Correspondence Carol J Bult. Email Published 14 August 2009 Received 22 May 2009 Genome Biology 2009 I0 R84 doi gb-2009-10-8-r84 Revisedj JuRy 2009 gy g Accepted 14 August 2009 The electronic version of this article is the complete one and can be found online at http 2009 10 8 R84 2009 Evsikov et al licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Linking biochemical genetic data to the reference genome for the laboratory mouse is important for comparative physiology and for developing mouse models of human biology and disease. We describe here a new database of curated metabolic pathways for the laboratory mouse called MouseCyc http . MouseCyc has been integrated with genetic and genomic data for the laboratory mouse available from the Mouse Genome Informatics database and with pathway data from other organisms including human. Rationale The availability of the nearly complete genome sequence for the laboratory mouse provides a powerful platform for predicting genes and other genome features and for exploring the biological significance of genome organization 1 . However building a catalog of genome annotations is just the first step in the post-genome biology 2 3 . Deriving new insights into complex biological processes using complete genomes and related genome-scale data will require understanding how individual biological units that comprise the genome for example genes and other genome features relate to one .

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