Through high quality curation we aim to integrate the wealth of Xenopus data into a single easily accessible computer framework that accelerates research, and facilitates the translation of this large amount of information into meaningful knowledge. The data in Xenbase must be comprehensive, accurate and up to date. Xenbase contains many different data types including; genomes and gene models, DNA, RNA and protein sequences, gene names and symbols, gene expression patterns, gene function, anatomy, orthology, reagents (MOs and antibodies), investigator information, phenotypes and disease associations. This data comes from the published literature, direct community submissions and from other databases (e.g. NCBI, JGI, OMIM). In order for the information in Xenbase to be computer readable, we index and annotate data using ontologies and standardized procedures that are the accepted best practices as shared across major model organism databases (MODs). This allows Xenopus data to be compared to other animals and to human disease gene and phenotypes. The majority of the curation effort is to read and annotate the published Xenopus literature. Xenbase contains a corpus of ~46,000 Xenopus papers, mirroring PubMed, but to date only about 10% of these have been curated, primarily for gene expression patterns. Preliminary analysis indicate that ~11,000 uncurated papers are likely to contain valuable high priority data and about 1,300 new Xenopus papers are published each year. In the Curation Component we will annotate this Xenopus research data.

National Institute of Health (NIH)
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Biotechnology Resource Grants (P41)
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Special Emphasis Panel (ZHD1)
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Cincinnati Children's Hospital Medical Center
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Patrushev, Ilya; James-Zorn, Christina; Ciau-Uitz, Aldo et al. (2018) New methods for computational decomposition of whole-mount in situ images enable effective curation of a large, highly redundant collection of Xenopus images. PLoS Comput Biol 14:e1006077
Karimi, Kamran; Wuitchik, Daniel M; Oldach, Matthew J et al. (2018) Distinguishing Species Using GC Contents in Mixed DNA or RNA Sequences. Evol Bioinform Online 14:1176934318788866
Karimi, Kamran; Fortriede, Joshua D; Lotay, Vaneet S et al. (2018) Xenbase: a genomic, epigenomic and transcriptomic model organism database. Nucleic Acids Res 46:D861-D868
James-Zorn, Christina; Ponferrada, Virgilio; Fisher, Malcolm E et al. (2018) Navigating Xenbase: An Integrated Xenopus Genomics and Gene Expression Database. Methods Mol Biol 1757:251-305
Vize, Peter D; Zorn, Aaron M (2017) Xenopus genomic data and browser resources. Dev Biol 426:194-199
Session, Adam M; Uno, Yoshinobu; Kwon, Taejoon et al. (2016) Genome evolution in the allotetraploid frog Xenopus laevis. Nature 538:336-343
Deans, Andrew R; Lewis, Suzanna E; Huala, Eva et al. (2015) Finding our way through phenotypes. PLoS Biol 13:e1002033
Vize, Peter D; Liu, Yu; Karimi, Kamran (2015) Database and Informatic Challenges in Representing Both Diploid and Tetraploid Xenopus Species in Xenbase. Cytogenet Genome Res 145:278-82
Grant, Ian M; Balcha, Dawit; Hao, Tong et al. (2015) The Xenopus ORFeome: A resource that enables functional genomics. Dev Biol 408:345-57
James-Zorn, Christina; Ponferrada, Virgillio G; Burns, Kevin A et al. (2015) Xenbase: Core features, data acquisition, and data processing. Genesis 53:486-97

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