219 related articles for article (PubMed ID: 31671773)
1. SL-BioDP: Multi-Cancer Interactive Tool for Prediction of Synthetic Lethality and Response to Cancer Treatment.
Deng X; Das S; Valdez K; Camphausen K; Shankavaram U
Cancers (Basel); 2019 Oct; 11(11):. PubMed ID: 31671773
[TBL] [Abstract][Full Text] [Related]
2. DiscoverSL: an R package for multi-omic data driven prediction of synthetic lethality in cancers.
Das S; Deng X; Camphausen K; Shankavaram U
Bioinformatics; 2019 Feb; 35(4):701-702. PubMed ID: 30059974
[TBL] [Abstract][Full Text] [Related]
3. Synthetic Lethal Drug Combinations Targeting Proteasome and Histone Deacetylase Inhibitors in TP53-Mutated Cancers.
Das S; Deng X; Camphausen K; Shankavaram U
Arch Cancer Biol Ther; 2020; 1(2):42-47. PubMed ID: 33163985
[TBL] [Abstract][Full Text] [Related]
4. Inferring synthetic lethal interactions from mutual exclusivity of genetic events in cancer.
Srihari S; Singla J; Wong L; Ragan MA
Biol Direct; 2015 Oct; 10():57. PubMed ID: 26427375
[TBL] [Abstract][Full Text] [Related]
5. Ranking novel cancer driving synthetic lethal gene pairs using TCGA data.
Ye H; Zhang X; Chen Y; Liu Q; Wei J
Oncotarget; 2016 Aug; 7(34):55352-55367. PubMed ID: 27438146
[TBL] [Abstract][Full Text] [Related]
6. Pan-Cancer Analysis of Potential Synthetic Lethal Drug Targets Specific to Alterations in DNA Damage Response.
Das S; Camphausen K; Shankavaram U
Front Oncol; 2019; 9():1136. PubMed ID: 31709193
[TBL] [Abstract][Full Text] [Related]
7. Link synthetic lethality to drug sensitivity of cancer cells.
Wang R; Han Y; Zhao Z; Yang F; Chen T; Zhou W; Wang X; Qi L; Zhao W; Guo Z; Gu Y
Brief Bioinform; 2019 Jul; 20(4):1295-1307. PubMed ID: 29300844
[TBL] [Abstract][Full Text] [Related]
8. In silico prediction of synthetic lethality by meta-analysis of genetic interactions, functions, and pathways in yeast and human cancer.
Wu M; Li X; Zhang F; Li X; Kwoh CK; Zheng J
Cancer Inform; 2014; 13(Suppl 3):71-80. PubMed ID: 25452682
[TBL] [Abstract][Full Text] [Related]
9. Multi-omics characterization of synthetic lethality-related molecular features: implications for SL-based therapeutic target screening.
Weng S; Ruan H
FEBS J; 2023 Mar; 290(6):1477-1480. PubMed ID: 36461713
[TBL] [Abstract][Full Text] [Related]
10. Predicting synthetic lethal interactions in human cancers using graph regularized self-representative matrix factorization.
Huang J; Wu M; Lu F; Ou-Yang L; Zhu Z
BMC Bioinformatics; 2019 Dec; 20(Suppl 19):657. PubMed ID: 31870274
[TBL] [Abstract][Full Text] [Related]
11. Synthetic lethality between gene defects affecting a single non-essential molecular pathway with reversible steps.
Zinovyev A; Kuperstein I; Barillot E; Heyer WD
PLoS Comput Biol; 2013 Apr; 9(4):e1003016. PubMed ID: 23592964
[TBL] [Abstract][Full Text] [Related]
12. Predicting cancer-specific vulnerability via data-driven detection of synthetic lethality.
Jerby-Arnon L; Pfetzer N; Waldman YY; McGarry L; James D; Shanks E; Seashore-Ludlow B; Weinstock A; Geiger T; Clemons PA; Gottlieb E; Ruppin E
Cell; 2014 Aug; 158(5):1199-1209. PubMed ID: 25171417
[TBL] [Abstract][Full Text] [Related]
13. SynLethDB: synthetic lethality database toward discovery of selective and sensitive anticancer drug targets.
Guo J; Liu H; Zheng J
Nucleic Acids Res; 2016 Jan; 44(D1):D1011-7. PubMed ID: 26516187
[TBL] [Abstract][Full Text] [Related]
14. Syn-lethality: an integrative knowledge base of synthetic lethality towards discovery of selective anticancer therapies.
Li XJ; Mishra SK; Wu M; Zhang F; Zheng J
Biomed Res Int; 2014; 2014():196034. PubMed ID: 24864230
[TBL] [Abstract][Full Text] [Related]
15. Synthetic lethality prediction in DNA damage repair, chromatin remodeling and the cell cycle using multi-omics data from cell lines and patients.
Markowska M; Budzinska MA; Coenen-Stass A; Kang S; Kizling E; Kolmus K; Koras K; Staub E; Szczurek E
Sci Rep; 2023 Apr; 13(1):7049. PubMed ID: 37120674
[TBL] [Abstract][Full Text] [Related]
16. SL-scan identifies synthetic lethal interactions in cancer using metabolic networks.
Zangene E; Marashi SA; Montazeri H
Sci Rep; 2023 Sep; 13(1):15763. PubMed ID: 37737478
[TBL] [Abstract][Full Text] [Related]
17. CSSLdb: Discovery of cancer-specific synthetic lethal interactions based on machine learning and statistic inference.
Dou Y; Ren Y; Zhao X; Jin J; Xiong S; Luo L; Xu X; Yang X; Yu J; Guo L; Liang T
Comput Biol Med; 2024 Mar; 170():108066. PubMed ID: 38310806
[TBL] [Abstract][Full Text] [Related]
18. Building high-resolution synthetic lethal networks: a 'Google map' of the cancer cell.
Paul JM; Templeton SD; Baharani A; Freywald A; Vizeacoumar FJ
Trends Mol Med; 2014 Dec; 20(12):704-15. PubMed ID: 25446836
[TBL] [Abstract][Full Text] [Related]
19. Systematic analysis of cancer-specific synthetic lethal interactions provides insight into personalized anticancer therapy.
Guo L; Dou Y; Xiang Y; Luo L; Xu X; Wang Q; Zhang Y; Liang T
FEBS J; 2023 Mar; 290(6):1531-1548. PubMed ID: 36181326
[TBL] [Abstract][Full Text] [Related]
20. SLGNN: synthetic lethality prediction in human cancers based on factor-aware knowledge graph neural network.
Zhu Y; Zhou Y; Liu Y; Wang X; Li J
Bioinformatics; 2023 Feb; 39(2):. PubMed ID: 36645245
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
