Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Shawn M, Gomez"'
Autor:
Matthew E. Berginski, Madison R. Jenner, Chinmaya U. Joisa, Gabriela Herrera Loeza, Brian T. Golitz, Matthew B. Lipner, Jack R. Leary, Naim Rashid, Gary L. Johnson, Jen Jen Yeh, Shawn M. Gomez
Publikováno v:
PeerJ, Vol 12, p e17797 (2024)
Numerous aspects of cellular signaling are regulated by the kinome—the network of over 500 protein kinases that guides and modulates information transfer throughout the cell. The key role played by both individual kinases and assemblies of kinases
Externí odkaz:
https://doaj.org/article/16b9aed8382349fc9144d2ba44859ea3
Autor:
Kevin A. Chen, Nina C. Nishiyama, Meaghan M. Kennedy Ng, Alexandria Shumway, Chinmaya U. Joisa, Matthew R. Schaner, Grace Lian, Caroline Beasley, Lee-Ching Zhu, Surekha Bantumilli, Muneera R. Kapadia, Shawn M. Gomez, Terrence S. Furey, Shehzad Z. Sheikh
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Pediatric Crohn’s disease (CD) is characterized by a severe disease course with frequent complications. We sought to apply machine learning-based models to predict risk of developing future complications in pediatric CD using ileal and col
Externí odkaz:
https://doaj.org/article/979e1b72de6f43b790ae2ed45066b834
Autor:
Chinmaya U. Joisa, Kevin A. Chen, Matthew E. Berginski, Brian T. Golitz, Madison R. Jenner, Gabriela Herrera Loeza, Jen Jen Yeh, Shawn M. Gomez
Publikováno v:
PeerJ, Vol 11, p e16342 (2023)
Protein kinase activity forms the backbone of cellular information transfer, acting both individually and as part of a broader network, the kinome. Their central role in signaling leads to kinome dysfunction being a common driver of disease, and in p
Externí odkaz:
https://doaj.org/article/8bc2b6d4dbfe4288a0ab2733a2068d82
Publikováno v:
PLoS Computational Biology, Vol 19, Iss 2, p e1010888 (2023)
Protein kinases play a vital role in a wide range of cellular processes, and compounds that inhibit kinase activity emerging as a primary focus for targeted therapy development, especially in cancer. Consequently, efforts to characterize the behavior
Externí odkaz:
https://doaj.org/article/bf65bcbbc5aa4e8aaa04e2f58422c4c3
Publikováno v:
International Journal of Molecular Sciences, Vol 23, Iss 9, p 4733 (2022)
Nuclear magnetic resonance (NMR) spectroscopy was used to monitor glutathione metabolism in alginate-encapsulated JM-1 hepatoma cells perfused with growth media containing [3,3′-13C2]-cystine. After 20 h of perfusion with labeled medium, the 13C NM
Externí odkaz:
https://doaj.org/article/a58cbe70233045228bd3862c9aa63e0e
Autor:
Kevin A, Chen, Chinmaya U, Joisa, Jonathan, Stem, Jose G, Guillem, Shawn M, Gomez, Muneera R, Kapadia
Publikováno v:
Dis Colon Rectum
Surgical site infection is a source of significant morbidity after colorectal surgery. Previous efforts to develop models that predict surgical site infection have had limited accuracy. Machine learning has shown promise in predicting post-operative
Autor:
Kevin A. Chen, Chinmaya U. Joisa, Karyn B. Stitzenberg, Jonathan Stem, Jose G. Guillem, Shawn M. Gomez, Muneera R. Kapadia
Publikováno v:
Journal of Gastrointestinal Surgery. 26:2342-2350
Autor:
Robert J. Mobley, Deepthi Raghu, Lauren D. Duke, Kayley Abell-Hart, Jon S. Zawistowski, Kyla Lutz, Shawn M. Gomez, Sujoy Roy, Ramin Homayouni, Gary L. Johnson, Amy N. Abell
Publikováno v:
Cell Reports, Vol 18, Iss 10, Pp 2387-2400 (2017)
The first epithelial-to-mesenchymal transition (EMT) occurs in trophoblast stem (TS) cells during implantation. Inactivation of the serine/threonine kinase MAP3K4 in TS cells (TSKI4 cells) induces an intermediate state of EMT, where cells retain stem
Externí odkaz:
https://doaj.org/article/c291185a476a427d8daabaff777c0e5d
Autor:
Kevin A. Chen, Matthew E. Berginski, Chirag S. Desai, Jose G. Guillem, Jonathan Stem, Shawn M. Gomez, Muneera R. Kapadia
Publikováno v:
Journal of Gastrointestinal Surgery. 26:1732-1742
Procedure-specific complications can have devastating consequences. Machine learning-based tools have the potential to outperform traditional statistical modeling in predicting their risk and guiding decision-making. We sought to develop and compare
Publikováno v:
Journal of the American College of Surgeons.