Cancer stem cells as a target population for drug discovery

2014 ◽  
Vol 6 (14) ◽  
pp. 1567-1585 ◽  
Author(s):  
Claire Bouvard ◽  
Colleen Barefield ◽  
Shoutian Zhu
Keyword(s):  
Stem Cells ◽  
Drug Discovery ◽  
Cancer Stem Cells ◽  
Target Population

scholarly journals Erratum: Drug Discovery Approaches to Target Wnt Signaling in Cancer Stem Cells

Oncotarget ◽  
2018 ◽  
Vol 9 (78) ◽  
pp. 34856-34856 ◽  
Author(s):  
Joshua C. Curtin ◽  
Matthew V. Lorenzi
Keyword(s):  
Stem Cells ◽  
Drug Discovery ◽  
Cancer Stem Cells ◽  
Wnt Signaling

scholarly journals Novel drug discovery system for cancer stem cells in human squamous cell carcinoma of the esophagus

2013 ◽  
Vol 31 (3) ◽  
pp. 1133-1138 ◽  
Author(s):  
YOSHIHIRO KANO ◽  
MASAMITSU KONNO ◽  
KOICHI KAWAMOTO ◽  
KEISUKE TAMARI ◽  
KAZUHIKO HAYASHI ◽  
...  
Keyword(s):  
Stem Cells ◽  
Squamous Cell Carcinoma ◽  
Drug Discovery ◽  
Cancer Stem Cells ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Carcinoma Of The Esophagus ◽  
Human Squamous Cell Carcinoma ◽  
Discovery System ◽  
Novel Drug

Conditional Generative Adversarial Networks to Model iPSC-Derived Cancer Stem Cells

2020 ◽  
Vol 24 (1) ◽  
pp. 134-141 ◽  
Author(s):  
Saori Aida ◽  
Hiroyuki Kameda ◽  
Sakae Nishisako ◽  
Tomonari Kasai ◽  
Atsushi Sato ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Stem Cells ◽  
Drug Discovery ◽  
Cancer Stem Cells ◽  
Low Cost ◽  
Generative Adversarial Networks ◽  
Cell Detection ◽  
Smart System ◽  
Adversarial Networks ◽  
Normal Image

The realization of effective and low-cost drug discovery is imperative to enable people to easily purchase and use medicines when necessary. This paper reports a smart system for detecting iPSC-derived cancer stem cells by using conditional generative adversarial networks. This system with artificial intelligence (AI) accepts a normal image from a microscope and transforms it into a corresponding fluorescent-marked fake image. The AI system learns 10,221 sets of paired pictures as input. Consequently, the system’s performance shows that the correlation between true fluorescent-marked images and fake fluorescent-marked images is at most 0.80. This suggests the fundamental validity and feasibility of our proposed system. Moreover, this research opens a new way for AI-based drug discovery in the process of iPSC-derived cancer stem cell detection.

scholarly journals Targeting cancer stem cells in drug discovery: Current state and future perspectives

2019 ◽  
Vol 11 (7) ◽  
pp. 398-420 ◽  
Author(s):  
Fang-Yu Du ◽  
Qi-Fan Zhou ◽  
Wen-Jiao Sun ◽  
Guo-Liang Chen
Keyword(s):  
Stem Cells ◽  
Drug Discovery ◽  
Cancer Stem Cells ◽  
Future Perspectives ◽  
Current State

Cancer stem cells as the relevant biomass for drug discovery

2010 ◽  
Vol 10 (4) ◽  
pp. 385-390 ◽  
Author(s):  
Raymond J Winquist ◽  
Brinley F Furey ◽  
Diane M Boucher
Keyword(s):  
Stem Cells ◽  
Drug Discovery ◽  
Cancer Stem Cells

scholarly journals Drug Discovery Approaches to Target Wnt Signaling in Cancer Stem Cells

Oncotarget ◽  
2010 ◽  
Vol 1 (7) ◽  
pp. 563-577 ◽  
Author(s):  
Joshua C. Curtin ◽  
Matthew V. Lorenzi
Keyword(s):  
Stem Cells ◽  
Drug Discovery ◽  
Cancer Stem Cells ◽  
Wnt Signaling
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