ArticleBioinformatics (Oxford, England)2016
Network-based pathway enrichment analysis with incomplete network information.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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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.
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Who cites it
31 citing papers in PubMed.
- A practical guide to functional enrichment analysis.Frontiers in bioinformatics · 2026Article
- Understanding and Advancing Wound Healing in the Era of Multi-Omic Technology.Bioengineering (Basel, Switzerland) · 2025Review
- Linear Dimensionality Reduction Methods for Analyzing Structured Biomedical Data: Existing Research and Future Opportunities.Wiley interdisciplinary reviews. Computational statistics · 2025Review
- Mitochondrial Dysfunction: Unraveling the Elusive Biology Behind Anti-TNF Response During Ulcerative Colitis.Inflammatory bowel diseases · 2025Article
- Bio-primed machine learning to enhance discovery of relevant biomarkers.NPJ precision oncology · 2025Article
- DNEA: an R package for fast and versatile data-driven network analysis of metabolomics data.BMC bioinformatics · 2024Article
- DeePathNet: A Transformer-Based Deep Learning Model Integrating Multiomic Data with Cancer Pathways.Cancer research communications · 2024Article
- CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data.Journal of visualized experiments : JoVE · 2023Article
- DRAGON: Determining Regulatory Associations using Graphical models on multi-Omic Networks.Nucleic acids research · 2023Article
- Article
- Metabolomics identifies shared lipid pathways in independent amyotrophic lateral sclerosis cohorts.Brain : a journal of neurology · 2022Article
- Review
- Information enhanced model selection for Gaussian graphical model with application to metabolomic data.Biostatistics (Oxford, England) · 2022Article
- Predicting causal genes from psychiatric genome-wide association studies using high-level etiological knowledge.Molecular psychiatry · 2022Article
- GPCRs Are Optimal Regulators of Complex Biological Systems and Orchestrate the Interface between Health and Disease.International journal of molecular sciences · 2021Review
- REHE: Fast variance components estimation for linear mixed models.Genetic epidemiology · 2021Article
- Integrative Analysis of Next-Generation Sequencing for Next-Generation Cancer Research toward Artificial Intelligence.Cancers · 2021Review
- netgsa: Fast computation and interactive visualization for topology-based pathway enrichment analysis.PLoS computational biology · 2021Article
- An Augmented High-Dimensional Graphical Lasso Method to Incorporate Prior Biological Knowledge for Global Network Learning.Frontiers in genetics · 2021Article
- Epigenetic loss of AOX1 expression via EZH2 leads to metabolic deregulations and promotes bladder cancer progression.Oncogene · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
motivationPathway enrichment analysis has become a key tool for biomedical researchers to gain insight into the underlying biology of differentially expressed genes, proteins and metabolites. It reduces complexity and provides a system-level view of changes in cellular activity in response to treatments and/or in disease states. Methods that use existing pathway network information have been shown to outperform simpler methods that only take into account pathway membership. However, despite significant progress in understanding the association amongst members of biological pathways, and expansion of data bases containing information about interactions of biomolecules, the existing network information may be incomplete or inaccurate and is not cell-type or disease condition-specific.
resultsWe propose a constrained network estimation framework that combines network estimation based on cell- and condition-specific high-dimensional Omics data with interaction information from existing data bases. The resulting pathway topology information is subsequently used to provide a framework for simultaneous testing of differences in expression levels of pathway members, as well as their interactions. We study the asymptotic properties of the proposed network estimator and the test for pathway enrichment, and investigate its small sample performance in simulated and real data settings. AVAILABILITY AND IMPLEMENTATION: The proposed method has been implemented in the R-package netgsa available on CRAN. CONTACT: jinma@upenn.eduSupplementary information: Supplementary data are available at Bioinformatics online.
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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.