Zobrazeno 1 - 10
of 999
pro vyhledávání: '"Robinson Peter N"'
Autor:
Cavalleri, Emanuele, Cabri, Alberto, Soto-Gomez, Mauricio, Bonfitto, Sara, Perlasca, Paolo, Gliozzo, Jessica, Callahan, Tiffany J., Reese, Justin, Robinson, Peter N, Casiraghi, Elena, Valentini, Giorgio, Mesiti, Marco
The "RNA world" represents a novel frontier for the study of fundamental biological processes and human diseases and is paving the way for the development of new drugs tailored to the patient's biomolecular characteristics. Although scientific data a
Externí odkaz:
http://arxiv.org/abs/2312.00183
Autor:
Groza, Tudor, Caufield, Harry, Gration, Dylan, Baynam, Gareth, Haendel, Melissa A, Robinson, Peter N, Mungall, Christopher J, Reese, Justin T
Objective: Clinical deep phenotyping and phenotype annotation play a critical role in both the diagnosis of patients with rare disorders as well as in building computationally-tractable knowledge in the rare disorders field. These processes rely on u
Externí odkaz:
http://arxiv.org/abs/2309.17169
Autor:
Callahan, Tiffany J., Tripodi, Ignacio J., Stefanski, Adrianne L., Cappelletti, Luca, Taneja, Sanya B., Wyrwa, Jordan M., Casiraghi, Elena, Matentzoglu, Nicolas A., Reese, Justin, Silverstein, Jonathan C., Hoyt, Charles Tapley, Boyce, Richard D., Malec, Scott A., Unni, Deepak R., Joachimiak, Marcin P., Robinson, Peter N., Mungall, Christopher J., Cavalleri, Emanuele, Fontana, Tommaso, Valentini, Giorgio, Mesiti, Marco, Gillenwater, Lucas A., Santangelo, Brook, Vasilevsky, Nicole A., Hoehndorf, Robert, Bennett, Tellen D., Ryan, Patrick B., Hripcsak, George, Kahn, Michael G., Bada, Michael, Baumgartner Jr, William A., Hunter, Lawrence E.
Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowle
Externí odkaz:
http://arxiv.org/abs/2307.05727
Autor:
Caufield, J. Harry, Hegde, Harshad, Emonet, Vincent, Harris, Nomi L., Joachimiak, Marcin P., Matentzoglu, Nicolas, Kim, HyeongSik, Moxon, Sierra A. T., Reese, Justin T., Haendel, Melissa A., Robinson, Peter N., Mungall, Christopher J.
Creating knowledge bases and ontologies is a time consuming task that relies on a manual curation. AI/NLP approaches can assist expert curators in populating these knowledge bases, but current approaches rely on extensive training data, and are not a
Externí odkaz:
http://arxiv.org/abs/2304.02711
Autor:
Caufield, J Harry, Putman, Tim, Schaper, Kevin, Unni, Deepak R, Hegde, Harshad, Callahan, Tiffany J, Cappelletti, Luca, Moxon, Sierra AT, Ravanmehr, Vida, Carbon, Seth, Chan, Lauren E, Cortes, Katherina, Shefchek, Kent A, Elsarboukh, Glass, Balhoff, James P, Fontana, Tommaso, Matentzoglu, Nicolas, Bruskiewich, Richard M, Thessen, Anne E, Harris, Nomi L, Munoz-Torres, Monica C, Haendel, Melissa A, Robinson, Peter N, Joachimiak, Marcin P, Mungall, Christopher J, Reese, Justin T
Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of knowledge graphs i
Externí odkaz:
http://arxiv.org/abs/2302.10800
Autor:
Callahan, Tiffany J., Stefanski, Adrianne L., Wyrwa, Jordan M., Zeng, Chenjie, Ostropolets, Anna, Banda, Juan M., Baumgartner Jr., William A., Boyce, Richard D., Casiraghi, Elena, Coleman, Ben D., Collins, Janine H., Deakyne-Davies, Sara J., Feinstein, James A., Haendel, Melissa A., Lin, Asiyah Y., Martin, Blake, Matentzoglu, Nicolas A., Meeker, Daniella, Reese, Justin, Sinclair, Jessica, Taneja, Sanya B., Trinkley, Katy E., Vasilevsky, Nicole A., Williams, Andrew, Zhang, Xingman A., Denny, Joshua C., Robinson, Peter N., Ryan, Patrick, Hripcsak, George, Bennett, Tellen D., Hunter, Lawrence E., Kahn, Michael G.
Background: Common data models solve many challenges of standardizing electronic health record (EHR) data, but are unable to semantically integrate all the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry o
Externí odkaz:
http://arxiv.org/abs/2209.04732
Autor:
Casiraghi, Elena, Wong, Rachel, Hall, Margaret, Coleman, Ben, Notaro, Marco, Evans, Michael D., Tronieri, Jena S., Blau, Hannah, Laraway, Bryan, Callahan, Tiffany J., Chan, Lauren E., Bramante, Carolyn T., Buse, John B., Moffitt, Richard A., Sturmer, Til, Johnson, Steven G., Shao, Yu Raymond, Reese, Justin, Robinson, Peter N., Paccanaro, Alberto, Valentini, Giorgio, Huling, Jared D., Wilkins, Kenneth, Bennet, Tell, Chute, Christopher, DeWitt, Peter, Gersing, Kenneth, Girvin, Andrew, Haendel, Melissa, Harper, Jeremy, Hajagos, Janos, Hong, Stephanie, Pfaff, Emily, Reusch, Jane, Antoniescu, Corneliu, Robaski, Kimberly
Healthcare datasets obtained from Electronic Health Records have proven to be extremely useful to assess associations between patients' predictors and outcomes of interest. However, these datasets often suffer from missing values in a high proportion
Externí odkaz:
http://arxiv.org/abs/2206.06444
Autor:
Cacheiro, Pilar, Lawson, Samantha, Van den Veyver, Ignatia B., Marengo, Gabriel, Zocche, David, Murray, Stephen A., Duyzend, Michael, Robinson, Peter N., Smedley, Damian
Publikováno v:
In Genetics in Medicine July 2024 26(7)