ArticleNPJ systems biology and applications2017
On the performance of de novo pathway enrichment.
Article in NPJ systems biology and applications, 2017. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
- Guiding questions to avoid data leakage in biological machine learning applications.Nature methods · 2024Review
- Lacking mechanistic disease definitions and corresponding association data hamper progress in network medicine and beyond.Nature communications · 2023Article
- Network-based approaches for modeling disease regulation and progression.Computational and structural biotechnology journal · 2023Review
- De novo identification of maximally deregulated subnetworks based on multi-omics data with DeRegNet.BMC bioinformatics · 2022Article
- TopoFun: a machine learning method to improve the functional similarity of gene co-expression modules.NAR genomics and bioinformatics · 2021Article
- Transcriptional landscape of cellular networks reveal interactions driving the dormancy mechanisms in cancer.Scientific reports · 2021Article
- A multi-objective genetic algorithm to find active modules in multiplex biological networks.PLoS computational biology · 2021Article
- Fostering reproducibility, reusability, and technology transfer in health informatics.iScience · 2021Review
- A systems pharmacology approach based on oncogenic signalling pathways to determine the mechanisms of action of natural products in breast cancer from transcriptome data.BMC complementary medicine and therapies · 2021Article
- NetMix: A Network-Structured Mixture Model for Reduced-Bias Estimation of Altered Subnetworks.Journal of computational biology : a journal of computational molecular cell biology · 2021Article
- Article
- Identification of significantly mutated subnetworks in the breast cancer genome.Scientific reports · 2021Article
- Multi-omics integration in biomedical research - A metabolomics-centric review.Analytica chimica acta · 2021Review
- KeyPathwayMineR:Frontiers in genetics · 2021Review
- Mapping Transcriptome Data to Protein-Protein Interaction Networks of Inflammatory Bowel Diseases Reveals Disease-Specific Subnetworks.Frontiers in genetics · 2021Article
- Molecular networks in Network Medicine: Development and applications.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- NOX5-induced uncoupling of endothelial NO synthase is a causal mechanism and theragnostic target of an age-related hypertension endotype.PLoS biology · 2020Article
- Exploring the SARS-CoV-2 virus-host-drug interactome for drug repurposing.Nature communications · 2020Article
- A Genome-Wide Integrative Association Study of DNA Methylation and Gene Expression Data and Later Life Cognitive Functioning in Monozygotic Twins.Frontiers in neuroscience · 2020Article
- From single drug targets to synergistic network pharmacology in ischemic stroke.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
De novo pathway enrichment is a powerful approach to discover previously uncharacterized molecular mechanisms in addition to already known pathways. To achieve this, condition-specific functional modules are extracted from large interaction networks. Here, we give an overview of the state of the art and present the first framework for assessing the performance of existing methods. We identified 19 tools and selected seven representative candidates for a comparative analysis with more than 12,000 runs, spanning different biological networks, molecular profiles, and parameters. Our results show that none of the methods consistently outperforms the others. To mitigate this issue for biomedical researchers, we provide guidelines to choose the appropriate tool for a given dataset. Moreover, our framework is the first attempt for a quantitative evaluation of de novo methods, which will allow the bioinformatics community to objectively compare future tools against the state of the art.
Identifiers
What OpenQuestion holds
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.