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 …

Connectivity mapping resources consist of signatures representing changes in cellular state
following systematic small-molecule, disease, gene, or other form of perturbations. Such …

Most gene expression datasets generated by individual researchers are too small to fully
benefit from unsupervised machine-learning methods. In the case of rare diseases, there …

We present Beyondcell, a computational methodology for identifying tumour cell
subpopulations with distinct drug responses in single-cell RNA-seq data and proposing …

Combination therapy is a promising clinical treatment strategy for cancer and other complex
diseases. Multiple drugs can target multiple proteins and pathways, greatly improving the …

Transcriptional perturbation signatures are valuable data sources for functional genomics.
Linking perturbation signatures to screenings opens the possibility to model cellular …

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

Transfer learning refers to the process of adapting a model trained on a source task to a
target task. While kernel methods are conceptually and computationally simple models that …

Matrix completion problems arise in many applications including recommendation systems,
computer vision, and genomics. Increasingly larger neural networks have been successful in …

Better drugs are needed for common epilepsies. Drug repurposing offers the potential of
significant savings in the time and cost of developing new treatments. In order to select the …