CyanoCyc cyanobacterial web portal

SciVal Topics Topic name Cyanobacteria; Synechocystis; Bacterial Protein Prominence percentile 95.943

CyanoCyc is a web portal that integrates an exceptionally rich database collection of information about cyanobacterial genomes with an extensive suite of bioinformatics tools. It was developed to address the needs of the cyanobacterial research and biotechnology communities. The 277 annotated cyanobacterial genomes currently in CyanoCyc are supplemented with computational inferences including predicted metabolic pathways, operons, protein complexes, and orthologs; and with data imported from external databases, such as protein features and Gene Ontology (GO) terms imported from UniProt. Five of the genome databases have undergone manual curation with input from more than a dozen cyanobacteria experts to correct errors and integrate information from more than 1,765 published articles. CyanoCyc has bioinformatics tools that encompass genome, metabolic pathway and regulatory informatics; omics data analysis; and comparative analyses, including visualizations of multiple genomes aligned at orthologous genes, and comparisons of metabolic networks for multiple organisms. CyanoCyc is a high-quality, reliable knowledgebase that accelerates scientists' work by enabling users to quickly find accurate information using its powerful set of search tools, to understand gene function through expert mini-reviews with citations, to acquire information quickly using its interactive visualization tools, and to inform better decision-making for fundamental and applied research.

We would like to acknowledge additional members of the research community who contributed to the CyanoCyc idea and review of curation of the Synechocystis sp. PCC 6803 (in alphabetical order): Devaki Bhaya, Danny Ducat, Jeff Elhai, George Espie, Martin Hagemann, Harvey Hou, Shoki Ito, Zhenxiong “Shaun” Jiang, Simab Kanwal, Tobias Pfennig, Amanda Shelton, Annegret Wilde, Erik Zinser. The author(s) declare financial support was received for the research, authorship, and/or publication of this article. We recognize and appreciate the funding for the following authors: PK, LM, RC, and SP from SRI International; DC acknowledges Canada Research Chair in Phytoplankton Ecophysiology; DL-S acknowledges funding from the Natural Environmental Research Council, UK (NE/X014428), and the Biotechnology and Biological Sciences Research Council, UK (BB/S020365/1). JC acknowledges funding as part of the Lawrence Livermore National Laboratory’s μBiospheres Science Focus Area FWP SCW1039 supported by the Genome Sciences Program of the U.S. Department of Energy’s Office of Biological and Environmental Research. This work was produced under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-JRNL-859262.

Peer reviewed