ArticleScientific reports2018
MTGO: PPI Network Analysis Via Topological and Functional Module Identification.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.
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66 citing papers in PubMed.
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- ASIC1a mediated nucleus pulposus cells pyroptosis and glycolytic crosstalk as a molecular basis for intervertebral disc degeneration.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025Review
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- Strategies for the drug development of cancer therapeutics.Frontiers in pharmacology · 2025Review
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- Identification of Autophagy-Related Candidate Genes in the Early Diagnosis of Alzheimer's Disease and Exploration of Potential Molecular Mechanisms.Molecular neurobiology · 2024Article
- Identification and verification of immune-related genes for diagnosing the progression of atherosclerosis and metabolic syndrome.BMC cardiovascular disorders · 2024Article
- CTHRC1 is a prognostic biomarker correlated with immune infiltration in head and neck squamous cell carcinoma.BMC oral health · 2024Article
- Molecular network mechanism in cerebral ischemia-reperfusion rats treated with human urine stem cells.Heliyon · 2024Article
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- Molecular mechanism of Achyranthis bidentatae radix and Morindae officinalis radix in osteoporosis therapy: An investigation based on network pharmacology, molecular docking, and molecular dynamics simulations.Biochemistry and biophysics reports · 2023Article
- Overexpression of C19orf48 correlates with poor prognosis in breast cancer.African health sciences · 2023Article
- DM-MOGA: a multi-objective optimization genetic algorithm for identifying disease modules of non-small cell lung cancer.BMC bioinformatics · 2023Article
6 more citing papers are in PubMed but not listed here.
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6 authors.
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Abstract
Protein-protein interaction (PPI) networks are viable tools to understand cell functions, disease machinery, and drug design/repositioning. Interpreting a PPI, however, it is a particularly challenging task because of network complexity. Several algorithms have been proposed for an automatic PPI interpretation, at first by solely considering the network topology, and later by integrating Gene Ontology (GO) terms as node similarity attributes. Here we present MTGO - Module detection via Topological information and GO knowledge, a novel functional module identification approach. MTGO let emerge the bimolecular machinery underpinning PPI networks by leveraging on both biological knowledge and topological properties. In particular, it directly exploits GO terms during the module assembling process, and labels each module with its best fit GO term, easing its functional interpretation. MTGO shows largely better results than other state of the art algorithms (including recent GO-based ones) when searching for small or sparse functional modules, while providing comparable or better results all other cases. MTGO correctly identifies molecular complexes and literature-consistent processes in an experimentally derived PPI network of Myocardial infarction. A software version of MTGO is available freely for non-commercial purposes at https://gitlab.com/d1vella/MTGO .
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