ArticleBriefings in bioinformatics2021
Reconciling multiple connectivity scores for drug repurposing.
Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- A functional genomics-pharmacotranscriptomics framework identifies host-directed anti-influenza agents.iScience · 2026Article
- Advances in high-throughput drug screening based on pharmacotranscriptomics.Journal of advanced research · 2026Review
- Single-Cell Computational Frameworks for Quantifying BET Bromodomain Inhibitor Resistance and Screening Re-Sensitizer Drugs in Triple-Negative Breast Cancer.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Artificial Intelligence in Drug Discovery and Development: Raising Quality per Decision.Pharmacopsychiatry · 2026Review
- Combinatorial prediction of therapeutic perturbations using causally inspired neural networks.Nature biomedical engineering · 2026Article
- Harnessing AI to fuse phenotypic signatures for drug target identification: progress in computational modeling.Briefings in bioinformatics · 2026Review
- The inferred functional connectome underlying circadian synchronization in the mouse suprachiasmatic nucleus.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A computational genetic- and transcriptomics-based study nominates drug repurposing candidates for the treatment of chronic pain.EBioMedicine · 2025Article
- Reconciling multiple connectivity-based systems biology methods for drug repurposing.Briefings in bioinformatics · 2025Review
- Integrative transcriptome-based drug repurposing in tuberculosis.bioRxiv : the preprint server for biology · 2025Article
- Integrated Computational and Functional Screening Identifies G9a Inhibitors for SETD2-mutant Leukemia.Genomics, proteomics & bioinformatics · 2025Article
- Translational regulation of SND1 governs endothelial homeostasis during stress.The Journal of clinical investigation · 2025Article
- Molecular Clustering of Metabolic Dysfunction-Associated Steatotic Liver Disease Based on Transcriptome Analysis.Diagnostics (Basel, Switzerland) · 2025Article
- Integrating pharmacogenomics and cheminformatics with diverse disease phenotypes for cell type-guided drug discovery.Genome medicine · 2025Article
- WebCMap: an R package for high-throughput connectivity analysis within the CMap framework.Bioinformatics advances · 2025Article
- Transcriptomic analysis revealsOncology letters · 2024Article
- Signature Search Polestar: a comprehensive drug repurposing method evaluation assistant for customized oncogenic signature.Bioinformatics (Oxford, England) · 2024Article
- Integrated transcriptomics- and structure-based drug repositioning identifies drugs with proteasome inhibitor properties.Scientific reports · 2024Article
- Optimizing in silico drug discovery: simulation of connected differential expression signatures and applications to benchmarking.Briefings in bioinformatics · 2024Article
- PharmGWAS: a GWAS-based knowledgebase for drug repurposing.Nucleic acids research · 2024Article
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Authors and funding
4 authors.
Funding
Abstract
The basis of several recent methods for drug repurposing is the key principle that an efficacious drug will reverse the disease molecular 'signature' with minimal side effects. This principle was defined and popularized by the influential 'connectivity map' study in 2006 regarding reversal relationships between disease- and drug-induced gene expression profiles, quantified by a disease-drug 'connectivity score.' Over the past 15 years, several studies have proposed variations in calculating connectivity scores toward improving accuracy and robustness in light of massive growth in reference drug profiles. However, these variations have been formulated inconsistently using various notations and terminologies even though they are based on a common set of conceptual and statistical ideas. Therefore, we present a systematic reconciliation of multiple disease-drug similarity metrics ($ES$, $css$, $Sum$, $Cosine$, $XSum$, $XCor$, $XSpe$, $XCos$, $EWCos$) and connectivity scores ($CS$, $RGES$, $NCS$, $WCS$, $Tau$, $CSS$, $EMUDRA$) by defining them using consistent notation and terminology. In addition to providing clarity and deeper insights, this coherent definition of connectivity scores and their relationships provides a unified scheme that newer methods can adopt, enabling the computational drug-development community to compare and investigate different approaches easily. To facilitate the continuous and transparent integration of newer methods, this article will be available as a live document (https://jravilab.github.io/connectivity_scores) coupled with a GitHub repository (https://github.com/jravilab/connectivity_scores) that any researcher can build on and push changes to.
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