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  1. Okuda S, Prince JP, Davis RE, Dally EL, Lee IM, Mogen B, et al.
    Plant Dis, 1997 Mar;81(3):301-305.
    PMID: 30861775 DOI: 10.1094/PDIS.1997.81.3.301
    Phytoplasmas (mycoplasmalike organisms, MLOs) associated with mitsuba (Japanese hone-wort) witches'-broom (JHW), garland chrysanthemum witches'-broom (GCW), eggplant dwarf (ED), tomato yellows (TY), marguerite yellows (MY), gentian witches'-broom (GW), and tsu-wabuki witches'-broom (TW) in Japan were investigated by polymerase chain reaction (PCR) amplification of DNA and restriction enzyme analysis of PCR products. The phytoplasmas could be separated into two groups, one containing strains JHW, GCW, ED, TY, and MY, and the other containing strains GW and TW, corresponding to two groups previously recognized on the basis of transmission by Macrosteles striifrons and Scleroracus flavopictus, respectively. The strains transmitted by M. striifrons were classified in 16S rRNA gene group 16SrI, which contains aster yellows and related phytoplasma strains. Strains GW and TW were classified in group 16SrIII, which contains phytoplasmas associated with peach X-disease, clover yellow edge, and related phytoplasmas. Digestion of amplified 16S rDNA with HpaII indicated that strains GW and TW were affiliated with subgroup 16SrIII-B, which contains clover yellow edge phytoplasma. All seven strains were distinguished from other phytoplasmas, including those associated with clover proliferation, ash yellows, elm yellows, and beet leafhopper-transmitted virescence in North America, and Malaysian periwinkle yellows and sweet potato witches'-broom in Asia.
  2. Vos RA, Katayama T, Mishima H, Kawano S, Kawashima S, Kim JD, et al.
    F1000Res, 2020;9:136.
    PMID: 32308977 DOI: 10.12688/f1000research.18236.1
    We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.
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