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 Resources>>Functional Annotation:
I. InterPro

InterPro provides functional analysis of proteins by classifying them into families and predicting domains and important sites. Its combines protein signatures from a number of member databases into a single searchable resource, capitalising on their individual strengths to produce a powerful integrated database and diagnostic tool [1].

Species Total Genes Annotated Genes by InterPro Involved InterPro Terms
Sesamum indicum var. Zhongzhi13 27,148 20,009 5,865

II. Gene Ontology (GO)

Gene Ontology: the framework for the model of biology. The GO defines concepts/classes used to describe gene function, and relationships between these concepts. It classifies functions along three aspects: (i).molecular function: molecular activities of gene products; (ii). cellular component: where gene products are active; (iii). biological process: pathways and larger processes made up of the activities of multiple gene products [2].

Species Total Genes Annotated Genes by GO Involved GO Terms
Sesamum indicum var. Zhongzhi13 27,148 14,477 1,780

III. KEGG

KEGG is a database resource for understanding high-level functions and utilities of the biological system, such as the cell, the organism and the ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies [3].

Species Total Genes Annotated Genes by KEGG Involved Pathways
Sesamum indicum var. Zhongzhi13 27,148 1,985 122

IV. MetaCyc

MetaCyc is a curated database of experimentally elucidated metabolic pathways from all domains of life. MetaCyc contains 2526 pathways from 2844 different organisms. MetaCyc contains pathways involved in both primary and secondary metabolism, as well as associated metabolites, reactions, enzymes, and genes. The goal of MetaCyc is to catalog the universe of metabolism by storing a representative sample of each experimentally elucidated pathway [4].

Species Total Genes Annotated Genes by MetaCyc Involved MetaCyc Terms
Sesamum indicum var. Zhongzhi13 27,148 1,351 577

 
Reference:

1. Robert D. Finn, Teresa K. Attwood, Patricia C. Babbitt, Alex Bateman, Peer Bork, Alan J. Bridge, Hsin-Yu Chang, Zsuzsanna Dosztányi, Sara El-Gebali, Matthew Fraser, Julian Gough, David Haft, Gemma L. Holliday, Hongzhan Huang, Xiaosong Huang, Ivica Letunic, Rodrigo Lopez, Shennan Lu, Aron Marchler-Bauer, Huaiyu Mi, Jaina Mistry, Darren A. Natale, Marco Necci, Gift Nuka, Christine A. Orengo, Youngmi Park, Sebastien Pesseat, Damiano Piovesan, Simon C. Potter, Neil D. Rawlings, Nicole Redaschi, Lorna Richardson, Catherine Rivoire, Amaia Sangrador-Vegas, Christian Sigrist, Ian Sillitoe, Ben Smithers, Silvano Squizzato, Granger Sutton, Narmada Thanki, Paul D Thomas, Silvio C. E. Tosatto, Cathy H. Wu, Ioannis Xenarios, Lai-Su Yeh, Siew-Yit Young, Alex L. Mitchell; InterPro in 2017—beyond protein family and domain annotations, Nucleic Acids Research, Volume 45, Issue D1, 4 January 2017, Pages D190–D199, https://doi.org/10.1093/nar/gkw1107.

2. The Gene Ontology Consortium; Gene Ontology Consortium: going forward, Nucleic Acids Research, Volume 43, Issue D1, 28 January 2015, Pages D1049–D1056, https://doi.org/10.1093/nar/gku1179.

3. Minoru Kanehisa, Miho Furumichi, Mao Tanabe, Yoko Sato, Kanae Morishima; KEGG: new perspectives on genomes, pathways, diseases and drugs, Nucleic Acids Research, Volume 45, Issue D1, 4 January 2017, Pages D353–D361, https://doi.org/10.1093/nar/gkw1092.

4. Ron Caspi, Richard Billington, Luciana Ferrer, Hartmut Foerster, Carol A. Fulcher, Ingrid M. Keseler, Anamika Kothari, Markus Krummenacker, Mario Latendresse, Lukas A. Mueller, Quang Ong, Suzanne Paley, Pallavi Subhraveti, Daniel S. Weaver, Peter D. Karp; The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases, Nucleic Acids Research, Volume 44, Issue D1, 4 January 2016, Pages D471–D480, https://doi.org/10.1093/nar/gkv1164.

 

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