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IGDD: a database of intronless genes in dicots.
Yan, Hanwei; Dai, Xiaogang; Feng, Kai; Ma, Qiuyue; Yin, Tongming.
Affiliation
  • Yan H; Key Laboratory of Forest Genetics & Biotechnology, Nanjing Forestry University, Nanjing, China.
  • Dai X; Laboratory of Modern Biotechnology, Anhui Agricultural University, Hefei, China.
  • Feng K; Key Laboratory of Forest Genetics & Biotechnology, Nanjing Forestry University, Nanjing, China.
  • Ma Q; Key Laboratory of Forest Genetics & Biotechnology, Nanjing Forestry University, Nanjing, China.
  • Yin T; Key Laboratory of Forest Genetics & Biotechnology, Nanjing Forestry University, Nanjing, China.
BMC Bioinformatics ; 17: 289, 2016 Jul 27.
Article in En | MEDLINE | ID: mdl-27465544
ABSTRACT

BACKGROUND:

Intronless genes are a significant characteristic of prokaryotes. Systematic identification and annotation are primary and crucial steps for determining the functions of intronless genes and understanding their occurrence in eukaryotes. DESCRIPTION In this paper, we describe the construction of the Intronless Genes Database in Dicots (IGDD; available at http//bio.njfu.edu.cn/igdd/ ), which contains data for five well-annotated plants including Arabidopsis thaliana, Carica papaya, Populus trichocarpa, Salix suchowensis and Vitis vinifera. Using highly visual settings, IGDD displays the structural and functional annotations, the homolog groups, the syntenic relationships, the expression patterns, and the statistical characteristics of intronless genes. In addition, useful tools such as an advanced search and local BLAST are available through a user-friendly and intuitive web interface.

CONCLUSION:

In conclusion, the IGDD provides a comprehensive and up-to-date platform for researchers to assist the exploration of intronless genes in dicot plants.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Magnoliopsida / Databases, Genetic Type of study: Prognostic_studies Language: En Journal: BMC Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2016 Type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Magnoliopsida / Databases, Genetic Type of study: Prognostic_studies Language: En Journal: BMC Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2016 Type: Article Affiliation country: China