Zobrazeno 1 - 10
of 409
pro vyhledávání: '"Hoyt, Charles"'
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:
Lobentanzer, Sebastian, Aloy, Patrick, Baumbach, Jan, Bohar, Balazs, Charoentong, Pornpimol, Danhauser, Katharina, Doğan, Tunca, Dreo, Johann, Dunham, Ian, Fernandez-Torras, Adrià, Gyori, Benjamin M., Hartung, Michael, Hoyt, Charles Tapley, Klein, Christoph, Korcsmaros, Tamas, Maier, Andreas, Mann, Matthias, Ochoa, David, Pareja-Lorente, Elena, Popp, Ferdinand, Preusse, Martin, Probul, Niklas, Schwikowski, Benno, Sen, Bünyamin, Strauss, Maximilian T., Turei, Denes, Ulusoy, Erva, Wodke, Judith Andrea Heidrun, Saez-Rodriguez, Julio
Standardising the representation of biomedical knowledge among all researchers is an insurmountable task, hindering the effectiveness of many computational methods. To facilitate harmonisation and interoperability despite this fundamental challenge,
Externí odkaz:
http://arxiv.org/abs/2212.13543
Autor:
Mohammad-Taheri, Sara, Tewari, Vartika, Kapre, Rohan, Rahiminasab, Ehsan, Sachs, Karen, Hoyt, Charles Tapley, Zucker, Jeremy, Vitek, Olga
Estimating a causal query from observational data is an essential task in the analysis of biomolecular networks. Estimation takes as input a network topology, a query estimation method, and observational measurements on the network variables. However
Externí odkaz:
http://arxiv.org/abs/2210.13423
Autor:
Matentzoglu, Nicolas, Goutte-Gattat, Damien, Tan, Shawn Zheng Kai, Balhoff, James P., Carbon, Seth, Caron, Anita R., Duncan, William D., Flack, Joe E., Haendel, Melissa, Harris, Nomi L., Hogan, William R, Hoyt, Charles Tapley, Jackson, Rebecca C., Kim, HyeongSik, Kir, Huseyin, Larralde, Martin, McMurry, Julie A., Overton, James A., Peters, Bjoern, Pilgrim, Clare, Stefancsik, Ray, Robb, Sofia MC, Toro, Sabrina, Vasilevsky, Nicole A, Walls, Ramona, Mungall, Christopher J., Osumi-Sutherland, David
Similar to managing software packages, managing the ontology life cycle involves multiple complex workflows such as preparing releases, continuous quality control checking, and dependency management. To manage these processes, a diverse set of tools
Externí odkaz:
http://arxiv.org/abs/2207.02056
The link prediction task on knowledge graphs without explicit negative triples in the training data motivates the usage of rank-based metrics. Here, we review existing rank-based metrics and propose desiderata for improved metrics to address lack of
Externí odkaz:
http://arxiv.org/abs/2203.07544
An emerging trend in representation learning over knowledge graphs (KGs) moves beyond transductive link prediction tasks over a fixed set of known entities in favor of inductive tasks that imply training on one graph and performing inference over a n
Externí odkaz:
http://arxiv.org/abs/2203.01520
Autor:
Rozemberczki, Benedek, Hoyt, Charles Tapley, Gogleva, Anna, Grabowski, Piotr, Karis, Klas, Lamov, Andrej, Nikolov, Andriy, Nilsson, Sebastian, Ughetto, Michael, Wang, Yu, Derr, Tyler, Gyori, Benjamin M
In this paper, we introduce ChemicalX, a PyTorch-based deep learning library designed for providing a range of state of the art models to solve the drug pair scoring task. The primary objective of the library is to make deep drug pair scoring models
Externí odkaz:
http://arxiv.org/abs/2202.05240
Autor:
Matentzoglu, Nicolas, Balhoff, James P., Bello, Susan M., Bizon, Chris, Brush, Matthew, Callahan, Tiffany J., Chute, Christopher G, Duncan, William D., Evelo, Chris T., Gabriel, Davera, Graybeal, John, Gray, Alasdair, Gyori, Benjamin M., Haendel, Melissa, Harmse, Henriette, Harris, Nomi L., Harrow, Ian, Hegde, Harshad, Hoyt, Amelia L., Hoyt, Charles T., Jiao, Dazhi, Jiménez-Ruiz, Ernesto, Jupp, Simon, Kim, Hyeongsik, Koehler, Sebastian, Liener, Thomas, Long, Qinqin, Malone, James, McLaughlin, James A., McMurry, Julie A., Moxon, Sierra, Munoz-Torres, Monica C., Osumi-Sutherland, David, Overton, James A., Peters, Bjoern, Putman, Tim, Queralt-Rosinach, Núria, Shefchek, Kent, Solbrig, Harold, Thessen, Anne, Tudorache, Tania, Vasilevsky, Nicole, Wagner, Alex H., Mungall, Christopher J.
Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major
Externí odkaz:
http://arxiv.org/abs/2112.07051
Autor:
Bonner, Stephen, Barrett, Ian P, Ye, Cheng, Swiers, Rowan, Engkvist, Ola, Hoyt, Charles Tapley, Hamilton, William L
Publikováno v:
Artificial Intelligence in the Life Sciences (2022): 100036
Knowledge Graphs (KG) and associated Knowledge Graph Embedding (KGE) models have recently begun to be explored in the context of drug discovery and have the potential to assist in key challenges such as target identification. In the drug discovery do
Externí odkaz:
http://arxiv.org/abs/2105.10488
Autor:
Bonner, Stephen, Barrett, Ian P, Ye, Cheng, Swiers, Rowan, Engkvist, Ola, Bender, Andreas, Hoyt, Charles Tapley, Hamilton, William L
Publikováno v:
Briefings in Bioinformatics, 2022
Drug discovery and development is a complex and costly process. Machine learning approaches are being investigated to help improve the effectiveness and speed of multiple stages of the drug discovery pipeline. Of these, those that use Knowledge Graph
Externí odkaz:
http://arxiv.org/abs/2102.10062