Gene Ontology
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Related Articles from SNS
Ignet 2.0 and Vignet: An Ontology-Driven Web Platform for Biomedical Gene Interaction Discovery and Visualization
Background: The expansion of biomedical literature demands systematic ontology-guided discovery of gene interactions, vaccine mechanisms, drug associations, and adverse events. Existing platforms such as STRING, DisGeNET, and PubTator fall short of providing a unified, freely accessible system that integrates ontology-based semantic interaction classification, vaccine-focused heterogeneous network construction, and Artificial Intelligence-assisted evidence retrieval. Ignet 2.0 and Vignet are...
Ontologizer 3: a cross-platform desktop application for frequentist and Bayesian GO enrichment analysis
We present Ontologizer 3, an easy-to-use cross-platform desktop application for Gene Ontology (GO) overrepresentation analysis. Ontologizer 3 offers two complementary methods. The first is a frequentist approach that evaluates GO terms individually using a one-sided Fisher's exact test, yielding term-level significance values.
Evidence-Aware Protein Complex Detection: Methods, Benchmarks, and Reproducibility Challenges
arXiv:2606.03178v1 Announce Type: new Abstract: Protein complexes are central units of cellular organization, yet their identification from protein-protein interaction (PPI) networks remains difficult because interactome maps are noisy, incomplete, context dependent, and unevenly annotated. This focused methodological review examines evidence-aware approaches that combine PPI topology with Gene Ontology (GO) annotations, expression profiles, subcellular localization, sequence or domain...
ECHO-PPI: Trustworthy AI for Evidence-Bundled Detection of Overlapping Protein Modules in Protein-Protein Interaction Networks
arXiv:2605.21216v2 Announce Type: replace Abstract: Protein-protein interaction networks provide a graph-level view of cellular organization, yet their functional modules are overlapping, noisy, and difficult to interpret from cluster assignments alone. Existing community-detection methods can recover candidate protein complexes, but they rarely explain why an individual protein is assigned to a specific module or whether that assignment should be treated as core, peripheral, or uncertain....
Interpretable Graph Kolmogorov-Arnold Networks for Multi-Cancer Classification and Biomarker Identification using Multi-Omics Data
arXiv:2503.22939v4 Announce Type: replace Abstract: The integration of heterogeneous multi-omics datasets at a systems level remains a central challenge for developing analytical and computational models in precision cancer diagnostics. This paper introduces Multi-Omics Graph Kolmogorov-Arnold Network (MOGKAN), a deep learning framework that utilizes messenger-RNA, micro-RNA sequences, and DNA methylation samples together with Protein-Protein Interaction (PPI) networks for cancer...
Coordinated neural, metabolic and muscular transcriptomic signatures associated with mite-biting behavior in honeybees (Apis mellifera L.)
Biting behavior is an important natural defense mechanism in honeybees (Apis mellifera) against Varroa destructor. Significant variation in this behavior exists across genetic lines of honeybees, with certain colonies exhibiting higher mite-biting activity than others. Selective breeding for enhanced biting behavior provides a promising strategy for sustainable mite control and colony resilience.
BRAINCELL-AID: An Agentic AI Created Brain Cell Type Resource for Community Annotation
arXiv:2510.17064v4 Announce Type: replace Abstract: Single-cell RNA sequencing has transformed our ability to identify diverse cell types and their transcriptomic signatures. However, annotating these signatures-especially those involving poorly characterized genes-remains a major challenge. Traditional methods, such as Gene Set Enrichment Analysis (GSEA), depend on well-curated annotations and often perform poorly in these contexts.
The Sorghum Lipid Database (SoLD): population-scale lipidomics linking environmental and genetic variation in the Sorghum Association Panel
Sorghum (Sorghum bicolor ) is a climate-resilient crop whose acclimation to nutrient limitation and low temperature likely involves extensive lipidome reconfiguration. Lipids are key membrane components, carbon and energy stores, and mediators of stress signaling, yet population-scale lipidomics data for sorghum are limited. We present the Sorghum Lipid Database (SoLD), a curated lipidomics resource from the Sorghum Association Panel grown under two field regimes: (i) a nutrient-sufficient...