Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data
There are no robust methods for systematically identifying mutation-specific synthetic lethal (SL) partners in cancer. Here, the authors develop a computational algorithm that uses pan-cancer data to detect mutation-andcancer-specific SL partners and they validate a novel SL interaction between muta...
Enregistré dans:
Auteurs principaux: | Subarna Sinha, Daniel Thomas, Steven Chan, Yang Gao, Diede Brunen, Damoun Torabi, Andreas Reinisch, David Hernandez, Andy Chan, Erinn B. Rankin, Rene Bernards, Ravindra Majeti, David L. Dill |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2017
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/e49e620b8adf451f9e5a7aa02173d0b8 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
The tumor therapy landscape of synthetic lethality
par: Biyu Zhang, et autres
Publié: (2021) -
RAD52: Paradigm of Synthetic Lethality and New Developments
par: Matthew J. Rossi, et autres
Publié: (2021) -
Harnessing synthetic lethality to predict the response to cancer treatment
par: Joo Sang Lee, et autres
Publié: (2018) -
Synthetic lethality between androgen receptor signalling and the PARP pathway in prostate cancer
par: Mohammad Asim, et autres
Publié: (2017) -
An in-silico approach to predict and exploit synthetic lethality in cancer metabolism
par: Iñigo Apaolaza, et autres
Publié: (2017)