ArticleBMC bioinformatics2013
Reverse causal reasoning: applying qualitative causal knowledge to the interpretation of high-throughput data.
Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 1 of them a synthesis that pooled it.
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Who cites it
54 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Causal network analysis of omics data using prior knowledge databases.Briefings in bioinformatics · 2025Pooled it
- GINv2.0: a comprehensive topological network integrating molecular interactions from multiple knowledge bases.NPJ systems biology and applications · 2024Article
- Benchmarking causal reasoning algorithms for gene expression-based compound mechanism of action analysis.BMC bioinformatics · 2023Article
- RNA-seq reveals potential gene biomarkers in fathead minnows (Environmental science. Processes & impacts · 2022Article
- Network- and enrichment-based inference of phenotypes and targets from large-scale disease maps.NPJ systems biology and applications · 2022Article
- Computational analyses of mechanism of action (MoA): data, methods and integration.RSC chemical biology · 2022Review
- Causal reasoning over knowledge graphs leveraging drug-perturbed and disease-specific transcriptomic signatures for drug discovery.PLoS computational biology · 2022Article
- Causal Biological Network Model for Inflammasome Signaling Applied for Interpreting Transcriptomic Changes in Various Inflammatory States.International journal of inflammation · 2022Article
- A Functional Network Model of the Metastasis Suppressor PEBP1/RKIP and Its Regulators in Breast Cancer Cells.Cancers · 2021Article
- Paving the way for application of next generation risk assessment to safety decision-making for cosmetic ingredients.Regulatory toxicology and pharmacology : RTP · 2021Article
- LINPS: a database for cancer-cell-specific perturbations of biological networks.Database : the journal of biological databases and curation · 2021Article
- Identification of Mucus-Associated Molecular Subtypes of Chronic Obstructive Pulmonary Disease: A Latent Profile Analysis Based on MUC5B-Associated Genes.Medical science monitor : international medical journal of experimental and clinical research · 2021Article
- The status of causality in biological databases: data resources and data retrieval possibilities to support logical modeling.Briefings in bioinformatics · 2021Article
- Urinary EGF and MCP-1 and risk of CKD after cardiac surgery.JCI insight · 2021Article
- DeltaNeTS+: elucidating the mechanism of drugs and diseases using gene expression and transcriptional regulatory networks.BMC bioinformatics · 2021Article
- Systems Toxicology Approach for Assessing Developmental Neurotoxicity in Larval Zebrafish.Frontiers in genetics · 2021Article
- Non-Coding RNAs in the Brain-Heart Axis: The Case of Parkinson's Disease.International journal of molecular sciences · 2020Review
- A Computational Approach for Mapping Heme Biology in the Context of Hemolytic Disorders.Frontiers in bioengineering and biotechnology · 2020Article
- Quantifying mechanisms in neurodegenerative diseases (NDDs) using candidate mechanism perturbation amplitude (CMPA) algorithm.BMC bioinformatics · 2019Article
- Navigating the disease landscape: knowledge representations for contextualizing molecular signatures.Briefings in bioinformatics · 2019Review
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGene expression profiling and other genome-scale measurement technologies provide comprehensive information about molecular changes resulting from a chemical or genetic perturbation, or disease state. A critical challenge is the development of methods to interpret these large-scale data sets to identify specific biological mechanisms that can provide experimentally verifiable hypotheses and lead to the understanding of disease and drug action.
resultsWe present a detailed description of Reverse Causal Reasoning (RCR), a reverse engineering methodology to infer mechanistic hypotheses from molecular profiling data. This methodology requires prior knowledge in the form of small networks that causally link a key upstream controller node representing a biological mechanism to downstream measurable quantities. These small directed networks are generated from a knowledge base of literature-curated qualitative biological cause-and-effect relationships expressed as a network. The small mechanism networks are evaluated as hypotheses to explain observed differential measurements. We provide a simple implementation of this methodology, Whistle, specifically geared towards the analysis of gene expression data and using prior knowledge expressed in Biological Expression Language (BEL). We present the Whistle analyses for three transcriptomic data sets using a publically available knowledge base. The mechanisms inferred by Whistle are consistent with the expected biology for each data set.
conclusionsReverse Causal Reasoning yields mechanistic insights to the interpretation of gene expression profiling data that are distinct from and complementary to the results of analyses using ontology or pathway gene sets. This reverse engineering algorithm provides an evidence-driven approach to the development of models of disease, drug action, and drug toxicity.
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