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ORCAE-AOCC:用于注释非洲孤儿作物基因组的集中式门户。

ORCAE-AOCC: A Centralized Portal for the Annotation of African Orphan Crop Genomes.

机构信息

Centre for Microbial Ecology and Genomics, Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria 0028, South Africa.

Centre for Bioinformatics and Computational Biology, Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria 0028, South Africa.

出版信息

Genes (Basel). 2019 Nov 20;10(12):950. doi: 10.3390/genes10120950.

DOI:10.3390/genes10120950
PMID:31757073
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6969924/
Abstract

ORCAE (Online Resource for Community Annotation of Eukaryotes) is a public genome annotation curation resource. ORCAE-AOCC is a branch that is dedicated to the genomes published as part of the African Orphan Crops Consortium (AOCC). The motivation behind the development of the ORCAE platform was to create a knowledge-based website where the research-community can make contributions to improve genome annotations. All changes to any given gene-model or gene description are stored, and the entire annotation history can be retrieved. Genomes can either be set to "public" or "restricted" mode; anonymous users can browse public genomes but cannot make any changes. Aside from providing a user- friendly interface to view genome annotations, the platform also includes tools and information (such as gene expression evidence) that enables authorized users to edit and validate genome annotations. The ORCAE-AOCC platform will enable various stakeholders from around the world to coordinate their efforts to annotate and study underutilized crops.

摘要

ORCAE(真核生物在线注释资源)是一个公共的基因组注释管理资源。ORCAE-AOCC 是一个分支,专门用于发布非洲孤儿作物联盟(AOCC)的基因组。开发 ORCAE 平台的动机是创建一个基于知识的网站,研究社区可以在其中做出贡献,以改进基因组注释。任何给定基因模型或基因描述的所有更改都将被存储,并且可以检索整个注释历史记录。基因组可以设置为“公共”或“受限”模式;匿名用户可以浏览公共基因组,但不能进行任何更改。除了提供用户友好的界面来查看基因组注释外,该平台还包括工具和信息(如基因表达证据),使授权用户能够编辑和验证基因组注释。ORCAE-AOCC 平台将使来自世界各地的各种利益相关者能够协调努力,对未充分利用的作物进行注释和研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232f/6969924/c04767d028e1/genes-10-00950-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232f/6969924/a15c9d0a9877/genes-10-00950-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232f/6969924/15bfa2f0d6b3/genes-10-00950-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232f/6969924/c04767d028e1/genes-10-00950-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232f/6969924/a15c9d0a9877/genes-10-00950-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232f/6969924/15bfa2f0d6b3/genes-10-00950-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232f/6969924/c04767d028e1/genes-10-00950-g003.jpg

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Planta. 2019 Sep;250(3):695-708. doi: 10.1007/s00425-019-03129-y. Epub 2019 Mar 13.
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Errors in long-read assemblies can critically affect protein prediction.长读长组装中的错误会严重影响蛋白质预测。
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