ArticleCPT: pharmacometrics & systems pharmacology2015
Relating Chemical Structure to Cellular Response: An Integrative Analysis of Gene Expression, Bioactivity, and Structural Data Across 11,000 Compounds.
Article in CPT: pharmacometrics & systems pharmacology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
29 citing papers in PubMed.
- Integrating network analysis and machine learning to elucidate chemical-induced pancreatic toxicity in zebrafish embryos.Toxicological sciences : an official journal of the Society of Toxicology · 2025Article
- Integrating pharmacogenomics and cheminformatics with diverse disease phenotypes for cell type-guided drug discovery.Genome medicine · 2025Article
- Beyond Tanimoto: a learned bioactivity similarity index enhances ligand discovery.Frontiers in bioinformatics · 2025Article
- BioAct-Het: A Heterogeneous Siamese Neural Network for Bioactivity Prediction Using Novel Bioactivity Representation.ACS omega · 2023Article
- Biomod2 modeling for predicting the potential ecological distribution of three Fritillaria species under climate change.Scientific reports · 2023Article
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- From drug repositioning to target repositioning: prediction of therapeutic targets using genetically perturbed transcriptomic signatures.Bioinformatics (Oxford, England) · 2022Article
- An integrated network representation of multiple cancer-specific data for graph-based machine learning.NPJ systems biology and applications · 2022Article
- Recent Advances in Cancer Drug Discovery Through the Use of Phenotypic Reporter Systems, Connectivity Mapping, and Pooled CRISPR Screening.Frontiers in pharmacology · 2022Review
- Ibrutinib Blocks YAP1 Activation and Reverses BRAF Inhibitor Resistance in Melanoma Cells.Molecular pharmacology · 2022Article
- Published anti-SARS-CoV-2 in vitro hits share common mechanisms of action that synergize with antivirals.Briefings in bioinformatics · 2021Article
- GraphDTI: A robust deep learning predictor of drug-target interactions from multiple heterogeneous data.Journal of cheminformatics · 2021Article
- An information-theoretic approach for measuring the distance of organ tissue samples using their transcriptomic signatures.Bioinformatics (Oxford, England) · 2021Article
- Article
- Predicting drug-induced transcriptome responses of a wide range of human cell lines by a novel tensor-train decomposition algorithm.Bioinformatics (Oxford, England) · 2019Article
- Systems Pharmacogenomic Landscape of Drug Similarities from LINCS data: Drug Association Networks.Scientific reports · 2019Article
- Leveraging Big Data to Transform Drug Discovery.Methods in molecular biology (Clifton, N.J.) · 2019Article
- Cardiovascular Disease Risk Varies by Birth Month in Canines.Scientific reports · 2018Article
- Rational screening of peroxisome proliferator-activated receptor-γ agonists from natural products: potential therapeutics for heart failure.Pharmaceutical biology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
A central premise in systems pharmacology is that structurally similar compounds have similar cellular responses; however, this principle often does not hold. One of the most widely used measures of cellular response is gene expression. By integrating gene expression data from Library of Integrated Network-based Cellular Signatures (LINCS) with chemical structure and bioactivity data from PubChem, we performed a large-scale correlation analysis of chemical structures and gene expression profiles of over 11,000 compounds taking into account confounding factors such as biological conditions (e.g., cell line, dose) and bioactivities. We found that structurally similar compounds do indeed yield similar gene expression profiles. There is an ∼20% chance that two structurally similar compounds (Tanimoto Coefficient ≥ 0.85) share significantly similar gene expression profiles. Regardless of structural similarity, two compounds tend to share similar gene expression profiles in a cell line when they are administrated at a higher dose or when the cell line is sensitive to both compounds.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.