Zobrazeno 1 - 10
of 222
pro vyhledávání: '"Casiraghi, Elena"'
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:
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:
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:
Pasquali, Sandro, Vallacchi, Viviana, Lalli, Luca, Collini, Paola, Barisella, Marta, Romagosa, Cleofe, Bague, Silvia, Coindre, Jean Michel, Dei Tos, Angelo Paolo, Palmerini, Emanuela, Quagliuolo, Vittorio, Martin-Broto, Javier, Lopez-Pousa, Antonio, Grignani, Giovanni, Blay, Jean-Yves, Beveridge, Robert Diaz, Casiraghi, Elena, Brich, Silvia, Renne, Salvatore Lorenzo, Bergamaschi, Laura, Vergani, Barbara, Sbaraglia, Marta, Casali, Paolo Giovanni, Rivoltini, Licia, Stacchiotti, Silvia, Gronchi, Alessandro
Publikováno v:
In eBioMedicine August 2024 106
Autor:
Cappelletti, Luca, Fontana, Tommaso, Casiraghi, Elena, Ravanmehr, Vida, Callahan, Tiffany J., Cano, Carlos, Joachimiak, Marcin P., Mungall, Christopher J., Robinson, Peter N., Reese, Justin, Valentini, Giorgio
Graph Representation Learning (GRL) methods opened new avenues for addressing complex, real-world problems represented by graphs. However, many graphs used in these applications comprise millions of nodes and billions of edges and are beyond the capa
Externí odkaz:
http://arxiv.org/abs/2110.06196
Autor:
Chan, Lauren E, Casiraghi, Elena, Reese, Justin, Harmon, Quaker E., Schaper, Kevin, Hegde, Harshad, Valentini, Giorgio, Schmitt, Charles, Motsinger-Reif, Alison, Hall, Janet E, Mungall, Christopher J, Robinson, Peter N, Haendel, Melissa A
Publikováno v:
In International Journal of Medical Informatics July 2024 187
Autor:
Valentini, Giorgio, Casiraghi, Elena, Cappelletti, Luca, Fontana, Tommaso, Reese, Justin, Robinson, Peter
The development of Graph Representation Learning methods for heterogeneous graphs is fundamental in several real-world applications, since in several contexts graphs are characterized by different types of nodes and edges. We introduce a an algorithm
Externí odkaz:
http://arxiv.org/abs/2101.01425
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