Tech-1 Technology Component 1 describes essential work on existing custom software. This work will add new functionality to the Xenbase database and allow us to represent both anatomical and gene expression phenotypes from Xenopus experiments using an EQ syntax as well as with GO annotations.
These aims will be achieved though software development at multiple levels of the Xenbase system, from building the database support for phenotypes all the way through to user interfaces. To build this we will use logic from other MODs, that like Xenabse use a GMOD/Chado schema and we will adapt the web-application and interface code that we have already established for gene expression. Our experienced development team, along with the new hires outlined in this proposal, will build phenotype representation into Xenbase in a 2 year time frame. We will add representation of phenotypes as changes in gene expression levels within another year. Adding content and collaborating with external resources to maximize the impact of these data in understanding the molecular basis of human disease will take an additional 2 years.

Public Health Relevance

The Technology Development-1 Component will build software and data base infrastructure to curate and display phenotypes from Xenopus experiments. This is essential in order to effectively use Xenopus for human disease modeling.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Biotechnology Resource Grants (P41)
Project #
5P41HD064556-08
Application #
9380971
Study Section
Special Emphasis Panel (ZHD1)
Project Start
Project End
Budget Start
2017-12-01
Budget End
2018-11-30
Support Year
8
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Cincinnati Children's Hospital Medical Center
Department
Type
DUNS #
071284913
City
Cincinnati
State
OH
Country
United States
Zip Code
45229
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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
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
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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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