Evolution of precision oncology‐guided treatment paradigms
R DasGupta, A Yap, EY Yaqing… - WIREs Mechanisms of …, 2023 - Wiley Online Library
Cancer treatment is gradually evolving from the classical use of nonspecific cytotoxic drugs
targeting generic mechanisms of cell growth and proliferation. Instead, new “patient‐specific …
targeting generic mechanisms of cell growth and proliferation. Instead, new “patient‐specific …
Trust me if you can: a survey on reliability and interpretability of machine learning approaches for drug sensitivity prediction in cancer
With the ever-increasing number of artificial intelligence (AI) systems, mitigating risks
associated with their use has become one of the most urgent scientific and societal issues …
associated with their use has become one of the most urgent scientific and societal issues …
Predicting drug activity against cancer cells by random forest models based on minimal genomic information and chemical properties
AP Lind, PC Anderson - PloS one, 2019 - journals.plos.org
A key goal of precision medicine is predicting the best drug therapy for a specific patient
from genomic information. In oncology, cancers that appear similar pathologically can vary …
from genomic information. In oncology, cancers that appear similar pathologically can vary …
DeepDSC: a deep learning method to predict drug sensitivity of cancer cell lines
High-throughput screening technologies have provided a large amount of drug sensitivity
data for a panel of cancer cell lines and hundreds of compounds. Computational …
data for a panel of cancer cell lines and hundreds of compounds. Computational …
KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images
The application of convolutional neural networks (ConvNets) to harness high-content
screening images or 2D compound representations is gaining increasing attention in drug …
screening images or 2D compound representations is gaining increasing attention in drug …
Linking drug target and pathway activation for effective therapy using multi-task learning
Despite the abundance of large-scale molecular and drug-response data, the insights
gained about the mechanisms underlying treatment efficacy in cancer has been in general …
gained about the mechanisms underlying treatment efficacy in cancer has been in general …
Deep learning prediction of chemical-induced dose-dependent and context-specific multiplex phenotype responses and its application to personalized alzheimer's …
Predictive modeling of drug-induced gene expressions is a powerful tool for phenotype-
based compound screening and drug repurposing. State-of-the-art machine learning …
based compound screening and drug repurposing. State-of-the-art machine learning …
Single nucleotide and copy number variants of cancer driver genes inform drug response in multiple cancers
Z Wang, H Gu, P Qin, J Wang - Plos one, 2024 - journals.plos.org
Due to the heterogeneity of cancer, precision medicine has been a major challenge for
cancer treatment. Determining medication regimens based on patient genotypes has …
cancer treatment. Determining medication regimens based on patient genotypes has …
Current advances and limitations of deep learning in anticancer drug sensitivity prediction
X Tan, Y Yu, K Duan, J Zhang, P Sun… - Current topics in …, 2020 - ingentaconnect.com
Anticancer drug screening can accelerate drug discovery to save the lives of cancer
patients, but cancer heterogeneity makes this screening challenging. The prediction of …
patients, but cancer heterogeneity makes this screening challenging. The prediction of …
Adult stem cells and anticancer therapy
AV Kalvelytė, A Imbrasaitė, N Krestnikova… - Advances in molecular …, 2017 - Elsevier
This chapter first describes the potential of stem cells in diverse biopharmaceutical
applications, such as replacement therapy, disease modeling, and drug development. On …
applications, such as replacement therapy, disease modeling, and drug development. On …