Phenotype-based compound screening has advantages over target-based drug discovery,
but is unscalable and lacks understanding of mechanism of drug action. A chemical-induced …

Chemical-induced gene expression profiles provide critical information of chemicals in a
biological system, thus offering new opportunities for drug discovery. Despite their success …

Pharmaceutical or phytopharmaceutical molecules rely on the interaction with one or more
specific molecular targets to induce their anticipated biological responses. Nonetheless …

Motivation LINCS L1000 dataset contains numerous cellular expression data induced by
large sets of perturbagens. Although it provides invaluable resources for drug discovery as …

High-quality data is crucial for accurate machine learning and actionable analytics, however,
mislabeled or noisy data is a common problem in many domains. Distinguishing low-from …

Computational modeling of perturbation biology identifies relationships between molecular
elements and cellular response, and an accurate understanding of these systems will …

A vast amount of public RNA-sequencing datasets have been generated and used widely to
study transcriptome mechanisms. These data offer precious opportunity for advancing …

Target-based high-throughput compound screening dominates conventional one-drug-one-
gene drug discovery process. However, the readout from the chemical modulation of a …

RNA-binding proteins (RBPs) may play a critical role in gene regulation in various diseases
or biological processes by controlling post-transcriptional events such as polyadenylation …

Over the years, the increasing accessibility of gene expression profiling data has paved the
way for targeted therapy as a promising approach in cancer treatment, utilizing targeted …