Zobrazeno 1 - 10
of 195
pro vyhledávání: '"Young Hwan Chang"'
Publikováno v:
Communications Biology, Vol 7, Iss 1, Pp 1-6 (2024)
Abstract Cyclic Immunofluorescence (CyCIF) can quantify multiple biomarkers, but panel capacity is limited by technical challenges. We propose a computational panel reduction approach that can impute the information content from 25 markers using only
Externí odkaz:
https://doaj.org/article/ad03cbe49d734938a2d088691bb306da
Autor:
Riley M. Whalen, Ashley N. Anderson, Jocelyn A. Jones, Zachary Sims, Young Hwan Chang, Michel A. Nederlof, Melissa H. Wong, Summer L. Gibbs
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Persistently high, worldwide mortality from cancer highlights the unresolved challenges of disease surveillance and detection that impact survival. Development of a non-invasive, blood-based biomarker would transform survival from cancer. We
Externí odkaz:
https://doaj.org/article/c30a16b38b9a4e1eb4e0ca802cee4797
Autor:
Çiğdem Ak, Zeynep Sayar, Guillaume Thibault, Erik A. Burlingame, M.J. Kuykendall, Jennifer Eng, Alex Chitsazan, Koei Chin, Andrew C. Adey, Christopher Boniface, Paul T. Spellman, George V. Thomas, Ryan P. Kopp, Emek Demir, Young Hwan Chang, Vasilis Stavrinides, Sebnem Ece Eksi
Publikováno v:
iScience, Vol 27, Iss 9, Pp 110668- (2024)
Summary: Mapping the spatial interactions of cancer, immune, and stromal cell states presents novel opportunities for patient stratification and for advancing immunotherapy. While single-cell studies revealed significant molecular heterogeneity in pr
Externí odkaz:
https://doaj.org/article/af29b6f146c548339d8565cc10e61ec6
Autor:
Zinab O. Doha, Xiaoyan Wang, Nicholas L. Calistri, Jennifer Eng, Colin J. Daniel, Luke Ternes, Eun Na Kim, Carl Pelz, Michael Munks, Courtney Betts, Sunjong Kwon, Elmar Bucher, Xi Li, Trent Waugh, Zuzana Tatarova, Dylan Blumberg, Aaron Ko, Nell Kirchberger, Jennifer A. Pietenpol, Melinda E. Sanders, Ellen M. Langer, Mu-Shui Dai, Gordon Mills, Koei Chin, Young Hwan Chang, Lisa M. Coussens, Joe W. Gray, Laura M. Heiser, Rosalie C. Sears
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-21 (2023)
Abstract Triple-negative breast cancer (TNBC) patients have a poor prognosis and few treatment options. Mouse models of TNBC are important for development of new therapies, however, few mouse models represent the complexity of TNBC. Here, we develop
Externí odkaz:
https://doaj.org/article/2f5efa1be7d149bcb492c236e0e02ed5
Publikováno v:
Communications Biology, Vol 6, Iss 1, Pp 1-12 (2023)
Abstract Time-lapse imaging is a powerful approach to gain insight into the dynamic responses of cells, but the quantitative analysis of morphological changes over time remains challenging. Here, we exploit the concept of “trajectory embedding” t
Externí odkaz:
https://doaj.org/article/c3cd13b8922241de89bb9f79380820f5
Autor:
Eun Na Kim, Phyllis Zixuan Chen, Dario Bressan, Monika Tripathi, Ahmad Miremadi, Massimiliano di Pietro, Lisa M. Coussens, Gregory J. Hannon, Rebecca C. Fitzgerald, Lizhe Zhuang, Young Hwan Chang
Publikováno v:
Cell Reports: Methods, Vol 3, Iss 10, Pp 100595- (2023)
Summary: Imaging mass cytometry (IMC) is a powerful technique capable of detecting over 30 markers on a single slide. It has been increasingly used for single-cell-based spatial phenotyping in a wide range of samples. However, it only acquires a rect
Externí odkaz:
https://doaj.org/article/310d138d2c38433c976e5760fa2c40f5
Autor:
Erik Burlingame, Luke Ternes, Jia-Ren Lin, Yu-An Chen, Eun Na Kim, Joe W. Gray, Young Hwan Chang
Publikováno v:
Frontiers in Bioinformatics, Vol 3 (2023)
Introduction: Tissue-based sampling and diagnosis are defined as the extraction of information from certain limited spaces and its diagnostic significance of a certain object. Pathologists deal with issues related to tumor heterogeneity since analyzi
Externí odkaz:
https://doaj.org/article/60189829c99e49eba6f2198e25d9a4ac
Autor:
Luke Ternes, Mark Dane, Sean Gross, Marilyne Labrie, Gordon Mills, Joe Gray, Laura Heiser, Young Hwan Chang
Publikováno v:
Communications Biology, Vol 5, Iss 1, Pp 1-10 (2022)
The Multi-Encoder Variational AutoEncoder (ME-VAE) is a computational model that can control for multiple transformational features in single-cell imaging data, enabling researchers to extract meaningful single-cell information and better separate he
Externí odkaz:
https://doaj.org/article/62591d36456a47f795a757db9843ff3a
Autor:
Marilyne Labrie, Allen Li, Allison Creason, Courtney Betts, Jamie Keck, Brett Johnson, Shamilene Sivagnanam, Christopher Boniface, Hongli Ma, Aurora Blucher, Young Hwan Chang, Koei Chin, Jacqueline Vuky, Alexander R. Guimaraes, Molly Downey, Jeong Youn Lim, Lina Gao, Kiara Siex, Swapnil Parmar, Annette Kolodzie, Paul T. Spellman, Jeremy Goecks, Lisa M. Coussens, Christopher L. Corless, Raymond Bergan, Joe W. Gray, Gordon B. Mills, Zahi I. Mitri
Publikováno v:
npj Precision Oncology, Vol 5, Iss 1, Pp 1-11 (2021)
Abstract In a pilot study, we evaluated the feasibility of real-time deep analysis of serial tumor samples from triple negative breast cancer patients to identify mechanisms of resistance and treatment opportunities as they emerge under therapeutic s
Externí odkaz:
https://doaj.org/article/6f75a6bf3b4848219df5905c62072ab5
Autor:
Eric A. Stahlberg, Mohamed Abdel-Rahman, Boris Aguilar, Alireza Asadpoure, Robert A. Beckman, Lynn L. Borkon, Jeffrey N. Bryan, Colleen M. Cebulla, Young Hwan Chang, Ansu Chatterjee, Jun Deng, Sepideh Dolatshahi, Olivier Gevaert, Emily J. Greenspan, Wenrui Hao, Tina Hernandez-Boussard, Pamela R. Jackson, Marieke Kuijjer, Adrian Lee, Paul Macklin, Subha Madhavan, Matthew D. McCoy, Navid Mohammad Mirzaei, Talayeh Razzaghi, Heber L. Rocha, Leili Shahriyari, Ilya Shmulevich, Daniel G. Stover, Yi Sun, Tanveer Syeda-Mahmood, Jinhua Wang, Qi Wang, Ioannis Zervantonakis
Publikováno v:
Frontiers in Digital Health, Vol 4 (2022)
We are rapidly approaching a future in which cancer patient digital twins will reach their potential to predict cancer prevention, diagnosis, and treatment in individual patients. This will be realized based on advances in high performance computing,
Externí odkaz:
https://doaj.org/article/46e800c638964bf3bdfa34d7236e108c