[HTML][HTML] Modelling of compound combination effects and applications to efficacy and toxicity: state-of-the-art, challenges and perspectives
Highlights•Review of the state-of-the-art in the field of compound combination modelling.•
Significance of quality control of large-scale combination screening data.•Strategies for …
Significance of quality control of large-scale combination screening data.•Strategies for …
A systematic literature review for the prediction of anticancer drug response using various machine‐learning and deep‐learning techniques
Computational methods have gained prominence in healthcare research. The accessibility
of healthcare data has greatly incited academicians and researchers to develop executions …
of healthcare data has greatly incited academicians and researchers to develop executions …
NeRD: a multichannel neural network to predict cellular response of drugs by integrating multidimensional data
X Cheng, C Dai, Y Wen, X Wang, X Bo, S He, S Peng - BMC medicine, 2022 - Springer
Background Considering the heterogeneity of tumors, it is a key issue in precision medicine
to predict the drug response of each individual. The accumulation of various types of drug …
to predict the drug response of each individual. The accumulation of various types of drug …
Algorithms for drug sensitivity prediction
Precision medicine entails the design of therapies that are matched for each individual
patient. Thus, predictive modeling of drug responses for specific patients constitutes a …
patient. Thus, predictive modeling of drug responses for specific patients constitutes a …
Predicting cancer drug response in vivo by learning an optimal feature selection of tumour molecular profiles
(1) Background: Inter-tumour heterogeneity is one of cancer's most fundamental features.
Patient stratification based on drug response prediction is hence needed for effective anti …
Patient stratification based on drug response prediction is hence needed for effective anti …
Identification of drug candidates and repurposing opportunities through compound–target interaction networks
Introduction: System-wide identification of both on-and off-targets of chemical probes
provides improved understanding of their therapeutic potential and possible adverse effects …
provides improved understanding of their therapeutic potential and possible adverse effects …
DWUT-MLP: Classification of anticancer drug response using various feature selection and classification techniques
Drug response classification constitutes a major challenge in personalized medicine. The
suitable drug selection for cancer patients is substantial and the drug response prediction is …
suitable drug selection for cancer patients is substantial and the drug response prediction is …
CTDN (convolutional temporal based deep‐neural network): an improvised stacked hybrid computational approach for anticancer drug response prediction
The characterization of drug-metabolizing enzymes is a significant problem for customized
therapy. It is important to choose the right drugs for cancer victims, and the ability to forecast …
therapy. It is important to choose the right drugs for cancer victims, and the ability to forecast …
Genetic interaction-based biomarkers identification for drug resistance and sensitivity in cancer cells
Y Han, C Wang, Q Dong, T Chen, F Yang, Y Liu… - … Therapy-Nucleic Acids, 2019 - cell.com
Cancer cells generally harbor hundreds of alterations in the cancer genomes and act as
crucial factors in the development and progression of cancer. Gene alterations in the cancer …
crucial factors in the development and progression of cancer. Gene alterations in the cancer …
Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma
NE Berlow, R Rikhi, M Geltzeiler, J Abraham… - BMC cancer, 2019 - Springer
Background Cancer patients with advanced disease routinely exhaust available clinical
regimens and lack actionable genomic medicine results, leaving a large patient population …
regimens and lack actionable genomic medicine results, leaving a large patient population …