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Progress toward a universal biomedical data translator

Clinical, biomedical, and translational science has reached an inflection point in the breadth and diversity of available data and the potential impact of such data to improve human health and well‐being. However, the data are often siloed, disorganized, and not broadly accessible due to discipline‐...

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Detalles Bibliográficos
Autores principales: Fecho, Karamarie, Thessen, Anne E., Baranzini, Sergio E., Bizon, Chris, Hadlock, Jennifer J., Huang, Sui, Roper, Ryan T., Southall, Noel, Ta, Casey, Watkins, Paul B., Williams, Mark D., Xu, Hao, Byrd, William, Dančík, Vlado, Duby, Marc P., Dumontier, Michel, Glusman, Gustavo, Harris, Nomi L., Hinderer, Eugene W., Hyde, Greg, Johs, Adam, Su, Andrew I., Qin, Guangrong, Zhu, Qian, Dougherty, Jennifer, Huang, Conrad, Magis, Andrew, Smith, Brett, Celebi, Remzi, Chen, Zhehuan, Azevedo, Ricardo De Miranda, Emonet, Vincent, Lee, Jay, Weng, Chunhua, Yilmaz, Arif, Kim, Keum Joo, Santos, Eugene, Tonstad, Lucas, Veenhuis, Luke, Yakaboski, Chase, Acevedo, Liliana, Carrell, Steven, Deutsch, Eric, Glen, Amy, Hoffman, Andrew, Koslicki, David, Kvarfordt, Lindsey, Liu, Zheng, Liu, Shaopeng, Ma, Chunyu, Mendoza, Luis, Muluka, Arun Teja, Womack, Finn, Wood, Erica, Roach, Jared, Goel, Prateek, Weber, Rosina, Williams, Andrew, Gormley, Joseph, Zisk, Tom, Hanspers, Kristina, Hoatlin, Maureen, Pico, Alexander, Riutta, Anders, Callaghan, Jackson, Xu, Colleen, Ahalt, Stanley C., Balhoff, Jim, Edwards, Stephen, Haaland, Perry, Knowles, Michael, Krishnamurthy, Ashok, Mandal, Meisha, Peden, David B., Pfaff, Emily, Schurman, Shepherd, Shrivastava, Shalki, Yi, Hong, Reilly, Jason, Kanwar, Richa, Cox, Steven, Vaidya, Gaurav, Wang, Max, Alkanaq, Ahmed, Costanzo, Maria, Koesterer, Ryan, Flannick, Jason, Burtt, Noel, Kluge, Alexandria, Rubin, Irit, Strasser, Michael “ Michi”, Chung, Lawrence, Kang, Jimin, Mantilla, Michelle, Muller, Sandrine, Persaud, Bria, Wei, Qi, Baumgartner, Andrew, Dai, Cheng, Duvvuri, Venkata, Mauldin, Denise, Shmulevich, Ilya, Brandon, Namdi, Greyber, Alon, Kebede, Yaphet, Korn, Daniel, Mesbah, Abrar, Owen, Phil, Sakaguchi, Rayn, Seitanakis, Sarah, Tropsha, Alexander, Viola, Adam, Hubal, Robert, Mersmann, Marian, Morton, Kenny, Yao, Yao, Lin, Jason, Avila, Ricardo, Wu, Chunlei, Cano, Marco Alvarado, Gardner, Vicki, Issabekova, Tursynay, McMurry, Julie, Schaper, Kevin, Baumgartner, William, Cohen, Kevin, Gatica, Edgar, Hunter, Lawrence, Price, Guthrie, He, Kaiwen, Henrickson, Jeff, Mamidi, Tarun, Might, Matthew, Osborne, John, Patton, Michael, Rosenblatt, Greg, Tran‐Nguyen, Thi, Crouse, Andrew, Belhu, Basazin, Conlin, Tom, Huellas‐Bruskiewicz, Kenneth, Rudavsky‐Brody, Nathaniel, Shrestha, Manil, Stillwell, Lisa, von Grotthuss, Marcin, Wang, Patrick, Xin, Jiwen Kevin, Zhou, Xinghua, Champion, James, Scott, Erik, Sharma, Priya, Sinha, Meghamala, Raj, Shruti, Mease, Philip, Peene, R. Carter, McClelland, Jason, Schmitt, Charles P., Leigh, Margaret, Corkill, Dan, Zhou, Eric, Alden, John, Massung, Jeffrey, Brandes, Mac Kenzie, Amin, Nada, Chen, Mei‐Jan, Crowder, Camerron, Crumbley, Mary E., Fehrmann, Nathaniel, Foksinska, Aleksandra M., Jenkins, Lindsay, Huls, Forest B., Jarrell, Matthew, Pollard, Elizabeth, Rucka, Sienna, Southern, Nicholas, Tinglin, Jillian, Whitlock, Jordan, Zheng, Marissa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9372428/
https://www.ncbi.nlm.nih.gov/pubmed/35611543
http://dx.doi.org/10.1111/cts.13301
Descripción
Sumario:Clinical, biomedical, and translational science has reached an inflection point in the breadth and diversity of available data and the potential impact of such data to improve human health and well‐being. However, the data are often siloed, disorganized, and not broadly accessible due to discipline‐specific differences in terminology and representation. To address these challenges, the Biomedical Data Translator Consortium has developed and tested a pilot knowledge graph‐based “Translator” system capable of integrating existing biomedical data sets and “translating” those data into insights intended to augment human reasoning and accelerate translational science. Having demonstrated feasibility of the Translator system, the Translator program has since moved into development, and the Translator Consortium has made significant progress in the research, design, and implementation of an operational system. Herein, we describe the current system’s architecture, performance, and quality of results. We apply Translator to several real‐world use cases developed in collaboration with subject‐matter experts. Finally, we discuss the scientific and technical features of Translator and compare those features to other state‐of‐the‐art, biomedical graph‐based question‐answering systems.