BioPAX – A community standard for pathway data sharing
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Summary
Thousands of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases, and this large amount of pathway data in a computable form will support visualization, analysis and biological discovery.
- Type
- article
- Published
- 2010-09-01
- Cited by
- 695
- References
- 104
- Access
- Open access
- OpenAlex
- https://openalex.org/W1969709265
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:52802817
Keywords
Computer science, Biological pathway, Biological data, Data exchange, Visualization
References
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- Data Mining in the MetaCyc Family of Pathway Databases
- Proteogenomic convergence for understanding cancer pathways and networks
- Updates in Rhea—a manually curated resource of biochemical reactions
- Predicting Protein Relationships to Human Pathways through a Relational Learning Approach Based on Simple Sequence Features
- Module Extraction for Efficient Object Queries over Ontologies with Large ABoxes
- Automated visualization of rule-based models
- Comprehensive network map of interferon gamma signaling
- Prospects for Declarative Mathematical Modeling of Complex Biological Systems
- Application of Semantic Web Technology to Establish Knowledge Management and Discovery in the Life Sciences
- Database and Visualization for Advanced Systems Biology
- Pathway Curation Support as an Information Extraction Task
- Integración de bases de datos genómicas: una aproximación basada en modelado conceptual
- BioModels Database: a repository of mathematical models of biological processes.
- Managing biological data in pathways and networks
- A knowledgebase resource for interleukin-17 family mediated signaling
- Approaches in Integrative Bioinformatics
- Knowledge-based scaling for biological models. (Généralisation de modèles métaboliques par connaissances)
- Cheminformatics for genome-scale metabolic reconstructions
- Enhancing systems biology models through semantic data integration
- Using large-scale text mining for a systematic reconstruction of molecular mechanisms of diseases : a case study in thyroid cancer
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