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AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture

Creator:

Harper, Lisa, Campbell, Jacqueline, Cannon, Steve, Carson, James, Condon, Bradford, Cooper, Laurel, Dunn, Nathan, Elsik, Christine G., Farmer, Andrew, Ficklin, Stephen P., Grant, David, Grau, Emily, Cannon, Ethalinda K. S., Herndon, Nic, Hu, Zhi-Liang, Humann, Jodi, Jaiswal, Pankaj, Jonquet, Clement, Laporte, Marie-Angelique, Larmande, Pierre, Lazo, Gerard, McCarthy, Fiona, Menda, Naama, Jung, Sook, Mungall, Christopher J., Munoz-Torres, Monica C., Naithani, Sushma, Nelson, Rex, Nesdill, Daureen, Park, Carissa, Reecy, James, Reiser, Leonore, Sanderson, Lacey-Anne, Sen, Taner Z., Poelchau, Monica, Staton, Margaret, Subramaniam, Sabarinath, Tello-Ruiz, Marcela Karey, Unda, Victor, Unni, Deepak, Wang, Liya, Ware, Doreen, Wegrzyn, Jill, Williams, Jason, Woodhouse, Margaret, Walls, Ramona, Yu, Jing, Main, Doreen, Andorf, Carson, Arnaud, Elizabeth, Berardini, Tanya Z., and Birkett, Clayton

Abstract:

The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require datamanagement plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated...

Resource Type:

Article
Finding Our Way through Phenotypes

Creator:

Deans, Andrew R., Lewis, Suzanna E., Huala, Eva, Anzaldo, Salvatore S., Ashburner, Michael, Balhoff, James P., Blackburn, David C., Blake, Judith A., Burleigh, J. Gordon, Chanet, Bruno, Cooper, Lauren D., Courtot, Mélanie, Csösz, Sándor, Cul, Hong, Dahdul, Wasila, Das, Sandip, Dececchi, T. Alexander, Dettal, Agnes, Diogo, Rui, Druzinsky, Robert E., Dumontier, Michel, Franz, Nico M., Friedrich, Frank, Gkoutos, George V., Haendel, Melissa, Harmon, Luke J., Hayamizu, Terry F., He, Yongqun, Hines, Heather M., Ibrahim, Nizar, Jackson, Laura M., Jaiswal, Pankaj, James-Zorn, Christina, Köhler, Sebastian, Lecointre, Guillaume, Lapp, Hilmar, Lawrence, Carolyn J., Le Novère, Nicolas, Lundberg, John G., Macklin, James, Mast, Austin R., Midford, Peter E., Mikó, István, Mungall, Christopher J., Oellrich, Anika, Osumi-Sutherland, David, Parkinson, Helen, Ramírez, Martín J., Richter, Stefan, Robinson, Peter N., Ruttenberg, Alan, Schulz, Katja S., Segerdell, Erik, Seltmann, Katja C., Sharkey, Michael J., Smith, Aaron D., Smith, Barry, Specht, Chelsea D., Squires, R. Burke, Thacker, Robert W., Thessen, Anne, Fernandez-Triana, Jose, Vihinen, Mauno, Vize, Peter D., Vogt, Lars, Wall, Christine E., Walls, Ramona L., Westerfeld, Monte, Wharton, Robert A., Wirkner, Christian S., Woolley, James B., Yoder, Matthew J., Zorn, Aaron M., and Mabee, Paula

Abstract:

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across...

Resource Type:

Article

ScholarsArchive@OSU

AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture

Finding Our Way through Phenotypes

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