FlyBase is the core genomic / genetic Model Organism Database (MOD) for the important biomedical model, Drosophila melanogaster and related species of flies. Drosophila is one of the premiere animal research systems and can be used very cost-effectively to help understand the etiology of human genetic diseases and is the closest experimental model that care provide insights into the biology of insect vectors of human disease (such as mosquitos that carry major infectious diseases such as malaria. West Nile Virus. The goals are twofold: (1) to provide a centralized resource for Drosophila genetic/genomic data and experimental reagents in order to enable Drosophila research to advance as rapidly as possible and (2) to provide these results to the broader biomedical research community to further their own research. FlyBase captures data from the primary scientific literature and from large-scale genome analysis and functional genomics community resource projects through annotation by FlyBase curators, direct user submissions and automated text-mining. FlyBase and collaborating informatics resources extensively share data thereby leveraging the output of each group. These heterogeneous data are organized into coherent datasets and integrated in a central database according to a series of ontology organizing systems. On a bi-monthly basis, these data are extracted from the central FlyBase database and served to the entire scientific community through a freely accessible FlyBase website, which is accessed millions of times each month. In addition to providing the research community to ttie corpus of FlyBase-captured data in ways that can be readily interrogated and browsed, FlyBase also maintains millions of links to other biomedical websites providing other relevant information. Over the proposed 5-year grant period, FlyBase expects to contribute to the enhancement of MOD interoperability and to work with a broad range of informatics resources and journal publishers to provide as rich a set of data and data-mining tools as possible to the biomedical research community.
FlyBase provides crucial data and informatic infrastructure to accelerate the pace of Drosophila research and for the broader biomedical sciences community to leverage these discoveries to further their own research. Drosophila is now a well-accepted experimental model for human disease research and is the closest genetic / genomic experimental model system for research on the insect vectors that carry human diseases.
| Li, Hongde; Hurlburt, Alexander J; Tennessen, Jason M (2018) A Drosophila model of combined D-2- and L-2-hydroxyglutaric aciduria reveals a mechanism linking mitochondrial citrate export with oncometabolite accumulation. Dis Model Mech 11: |
| Yadav, Shruti; Gupta, Sonali; Eleftherianos, Ioannis (2018) Differential Regulation of Immune Signaling and Survival Response in Drosophila melanogaster Larvae upon Steinernema carpocapsae Nematode Infection. Insects 9: |
| Rey, Alix J; Attrill, Helen; Marygold, Steven J et al. (2018) Using FlyBase to Find Functionally Related Drosophila Genes. Methods Mol Biol 1757:493-512 |
| Thurmond, Jim; Goodman, Joshua L; Strelets, Victor B et al. (2018) FlyBase 2.0: the next generation. Nucleic Acids Res : |
| Howe, Douglas G; Blake, Judith A; Bradford, Yvonne M et al. (2018) Model organism data evolving in support of translational medicine. Lab Anim (NY) 47:277-289 |
| The Gene Ontology Consortium (2018) The Gene Ontology Resource: 20 years and still GOing strong. Nucleic Acids Res : |
| The RNAcentral Constortium (2018) RNAcentral: a hub of information for non-coding RNA sequences. Nucleic Acids Res : |
| Marygold, Steven J; Attrill, Helen; Lasko, Paul (2017) The translation factors of Drosophila melanogaster. Fly (Austin) 11:65-74 |
| Hu, Yanhui; Comjean, Aram; Mohr, Stephanie E et al. (2017) Gene2Function: An Integrated Online Resource for Gene Function Discovery. G3 (Bethesda) 7:2855-2858 |
| Marygold, Steven J; Antonazzo, Giulia; Attrill, Helen et al. (2016) Exploring FlyBase Data Using QuickSearch. Curr Protoc Bioinformatics 56:1.31.1-1.31.23 |
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