Geometric network analysis provides prognostic information in patients with high grade serous carcinoma of the ovary treated with immune checkpoint inhibitors
Abstract Network analysis methods can potentially quantify cancer aberrations in gene networks without introducing fitted parameters or variable selection. A new network curvature-based method is introduced to provide an integrated measure of variability within cancer gene networks. The method is ap...
Guardado en:
Autores principales: | Rena Elkin, Jung Hun Oh, Ying L. Liu, Pier Selenica, Britta Weigelt, Jorge S. Reis-Filho, Dmitriy Zamarin, Joseph O. Deasy, Larry Norton, Arnold J. Levine, Allen R. Tannenbaum |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/14677a3e0f704e37a93284a2df2fb8ea |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Targeting galectin-3 with a high-affinity antibody for inhibition of high-grade serous ovarian cancer and other MUC16/CA-125-expressing malignancies
por: Marina Stasenko, et al.
Publicado: (2021) -
Molecular analysis of high-grade serous ovarian carcinoma with and without associated serous tubal intra-epithelial carcinoma
por: Jennifer Ducie, et al.
Publicado: (2017) -
Both fallopian tube and ovarian surface epithelium are cells-of-origin for high-grade serous ovarian carcinoma
por: Shuang Zhang, et al.
Publicado: (2019) -
High grade serous ovarian carcinomas originate in the fallopian tube
por: S. Intidhar Labidi-Galy, et al.
Publicado: (2017) -
GRADED CRITERIA OF DIAGNOSTICS AND PREDICTION OF CENTRAL SEROUS CHORIORETINOPATHY OUTCOME
por: A. G. Shchuko, et al.
Publicado: (2016)