ArticleSource code for biology and medicine2012
PathNet: a tool for pathway analysis using topological information.
Article in Source code for biology and medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed, 79 citations in OpenAlex.
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- Gene set correlation enrichment analysis for interpreting and annotating gene expression profiles.Nucleic acids research · 2024Article
- CellGO: a novel deep learning-based framework and webserver for cell-type-specific gene function interpretation.Briefings in bioinformatics · 2023Article
- ActivePPI: quantifying protein-protein interaction network activity with Markov random fields.Bioinformatics (Oxford, England) · 2023Article
- A comprehensive survey of the approaches for pathway analysis using multi-omics data integration.Briefings in bioinformatics · 2022Review
- Bioinformatics roadmap for therapy selection in cancer genomics.Molecular oncology · 2022Review
- CTpathway: a CrossTalk-based pathway enrichment analysis method for cancer research.Genome medicine · 2022Article
- Nine quick tips for pathway enrichment analysis.PLoS computational biology · 2022Article
- On the influence of several factors on pathway enrichment analysis.Briefings in bioinformatics · 2022Review
- Identifying cancer pathway dysregulations using differential causal effects.Bioinformatics (Oxford, England) · 2022Article
- rPAC: Route based pathway analysis for cohorts of gene expression data sets.Methods (San Diego, Calif.) · 2022Article
- PAGER Web APP: An Interactive, Online Gene Set and Network Interpretation Tool for Functional Genomics.Frontiers in genetics · 2022Article
- netgsa: Fast computation and interactive visualization for topology-based pathway enrichment analysis.PLoS computational biology · 2021Article
- SIGNAL: A web-based iterative analysis platform integrating pathway and network approaches optimizes hit selection from genome-scale assays.Cell systems · 2021Article
- Predicting mechanism of action of cellular perturbations with pathway activity signatures.Bioinformatics (Oxford, England) · 2020Article
- Integrative systems and functional analyses reveal a role of dopaminergic signaling in myelin pathogenesis.Journal of translational medicine · 2020Article
- Gene Set Analysis: Challenges, Opportunities, and Future Research.Frontiers in genetics · 2020Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
unlabelled
backgroundIdentification of canonical pathways through enrichment of differentially expressed genes in a given pathway is a widely used method for interpreting gene lists generated from high-throughput experimental studies. However, most algorithms treat pathways as sets of genes, disregarding any inter- and intra-pathway connectivity information, and do not provide insights beyond identifying lists of pathways.
resultsWe developed an algorithm (PathNet) that utilizes the connectivity information in canonical pathway descriptions to help identify study-relevant pathways and characterize non-obvious dependencies and connections among pathways using gene expression data. PathNet considers both the differential expression of genes and their pathway neighbors to strengthen the evidence that a pathway is implicated in the biological conditions characterizing the experiment. As an adjunct to this analysis, PathNet uses the connectivity of the differentially expressed genes among all pathways to score pathway contextual associations and statistically identify biological relations among pathways. In this study, we used PathNet to identify biologically relevant results in two Alzheimer's disease microarray datasets, and compared its performance with existing methods. Importantly, PathNet identified de-regulation of the ubiquitin-mediated proteolysis pathway as an important component in Alzheimer's disease progression, despite the absence of this pathway in the standard enrichment analyses.
conclusionsPathNet is a novel method for identifying enrichment and association between canonical pathways in the context of gene expression data. It takes into account topological information present in pathways to reveal biological information. PathNet is available as an R workspace image from http://www.bhsai.org/downloads/pathnet/.
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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.