scDrug+: predicting drug-responses using single-cell transcriptomics and molecular structure.

Biomed Pharmacother

Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taiwan; Taiwan AI Labs, Taipei 10351, Taiwan; Department of Life Science, National Taiwan University, Taipei 106, Taiwan; Center for Computational and Systems Biology, National Taiwan University, Taipei 106, Taiwan; Center for Advanced Computing and Imaging in Biomedicine, National Taiwan University, Taipei 106, Taiwan. Electronic address:

Published: August 2024

Predicting drug responses based on individual transcriptomic profiles holds promise for refining prognosis and advancing precision medicine. Although many studies have endeavored to predict the responses of known drugs to novel transcriptomic profiles, research into predicting responses for newly discovered drugs remains sparse. In this study, we introduce scDrug+, a comprehensive pipeline that seamlessly integrates single-cell analysis with drug-response prediction. Importantly, scDrug+ is equipped to predict the response of new drugs by analyzing their molecular structures. The open-source tool is available as a Docker container, ensuring ease of deployment and reproducibility. It can be accessed at https://github.com/ailabstw/scDrugplus.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.biopha.2024.117070DOI Listing

Publication Analysis

Top Keywords

transcriptomic profiles
8
scdrug+ predicting
4
predicting drug-responses
4
drug-responses single-cell
4
single-cell transcriptomics
4
transcriptomics molecular
4
molecular structure
4
structure predicting
4
predicting drug
4
drug responses
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!