Deep learning for drug response prediction in cancer
Predicting the sensitivity of tumors to specific anti-cancer treatments is a challenge of
paramount importance for precision medicine. Machine learning (ML) algorithms can be …
paramount importance for precision medicine. Machine learning (ML) algorithms can be …
The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation
Background To evaluate binary classifications and their confusion matrices, scientific
researchers can employ several statistical rates, accordingly to the goal of the experiment …
researchers can employ several statistical rates, accordingly to the goal of the experiment …
[HTML][HTML] Network biology and artificial intelligence drive the understanding of the multidrug resistance phenotype in cancer
B Bueschbell, AB Caniceiro, PMS Suzano… - Drug Resistance …, 2022 - Elsevier
Globally with over 10 million deaths per year, cancer is the most transversal disease across
countries, cultures, and ethnicities, affecting both developed and developing regions …
countries, cultures, and ethnicities, affecting both developed and developing regions …
Predicting synergism of cancer drug combinations using NCI-ALMANAC data
P Sidorov, S Naulaerts, J Ariey-Bonnet… - Frontiers in …, 2019 - frontiersin.org
Drug combinations are of great interest for cancer treatment. Unfortunately, the discovery of
synergistic combinations by purely experimental means is only feasible on small sets of …
synergistic combinations by purely experimental means is only feasible on small sets of …
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 …
Predicting the formation of NADES using a transformer-based model
The application of natural deep eutectic solvents (NADES) in the pharmaceutical,
agricultural, and food industries represents one of the fastest growing fields of green …
agricultural, and food industries represents one of the fastest growing fields of green …
Computational approaches in cancer multidrug resistance research: Identification of potential biomarkers, drug targets and drug-target interactions
Like physics in the 19th century, biology and molecular biology in particular, has been
fertilized and enhanced like few other scientific fields, by the incorporation of mathematical …
fertilized and enhanced like few other scientific fields, by the incorporation of mathematical …
KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images
I Cortés-Ciriano, A Bender - Journal of cheminformatics, 2019 - Springer
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 …
Paclitaxel response can be predicted with interpretable multi-variate classifiers exploiting DNA-methylation and miRNA data
A Bomane, A Gonçalves, PJ Ballester - Frontiers in genetics, 2019 - frontiersin.org
To address the problem of resistance to paclitaxel treatment, we have investigated to which
extent is possible to predict Breast Cancer (BC) patient response to this drug. We carried out …
extent is possible to predict Breast Cancer (BC) patient response to this drug. We carried out …
PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data
E Piñeiro-Yáñez, M Reboiro-Jato, G Gómez-López… - Genome medicine, 2018 - Springer
Background Large-sequencing cancer genome projects have shown that tumors have
thousands of molecular alterations and their frequency is highly heterogeneous. In such …
thousands of molecular alterations and their frequency is highly heterogeneous. In such …