ArticleBMC systems biology2013
Precise generation of systems biology models from KEGG pathways.
Article in BMC systems biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 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
31 citing papers in PubMed.
- Platelet Proteomes, Pathways, and Phenotypes as Informants of Vascular Wellness and Disease.Arteriosclerosis, thrombosis, and vascular biology · 2021Review
- KEGG2Net: Deducing gene interaction networks and acyclic graphs from KEGG pathways.EMBnet.journal · 2021Article
- Identification of Pre-Diagnostic Metabolic Patterns for Glioma Using Subset Analysis of Matched Repeated Time Points.Cancers · 2020Article
- Closing the gap between formats for storing layout information in systems biology.Briefings in bioinformatics · 2020Article
- Why do anti-inflammatory signals of bone marrow-derived stromal cells improve neurodegenerative conditions where anti-inflammatory drugs fail?Journal of neural transmission (Vienna, Austria : 1996) · 2020Review
- MEMOTE for standardized genome-scale metabolic model testing.Nature biotechnology · 2020Article
- Exploring Integrative Analysis Using the BioMedical Evidence Graph.JCO clinical cancer informatics · 2020Article
- Pathway Commons 2019 Update: integration, analysis and exploration of pathway data.Nucleic acids research · 2020Article
- Finding MEMo: minimum sets of elementary flux modes.Journal of mathematical biology · 2019Article
- Transcriptome and miRNA analyses of the response to Corynespora cassiicola in cucumber.Scientific reports · 2018Article
- From word models to executable models of signaling networks using automated assembly.Molecular systems biology · 2017Article
- Simulation and visualization of multiple KEGG pathways using BioNSi.F1000Research · 2017Article
- A Comprehensive Gene Expression Meta-analysis Identifies Novel Immune Signatures in Rheumatoid Arthritis Patients.Frontiers in immunology · 2017Article
- Transcriptional profiling analysis of Spodoptera litura larvae challenged with Vip3Aa toxin and possible involvement of trypsin in the toxin activation.Scientific reports · 2016Article
- Taking Bioinformatics to Systems Medicine.Methods in molecular biology (Clifton, N.J.) · 2016Review
- SBMLsqueezer 2: context-sensitive creation of kinetic equations in biochemical networks.BMC systems biology · 2015Article
- High-throughput sequencing of small RNAs and anatomical characteristics associated with leaf development in celery.Scientific reports · 2015Article
- Mimoza: web-based semantic zooming and navigation in metabolic networks.BMC systems biology · 2015Article
- De novo assembly, transcriptome characterization, lignin accumulation, and anatomic characteristics: novel insights into lignin biosynthesis during celery leaf development.Scientific reports · 2015Article
- Comparison of human cell signaling pathway databases--evolution, drawbacks and challenges.Database : the journal of biological databases and curation · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe KEGG PATHWAY database provides a plethora of pathways for a diversity of organisms. All pathway components are directly linked to other KEGG databases, such as KEGG COMPOUND or KEGG REACTION. Therefore, the pathways can be extended with an enormous amount of information and provide a foundation for initial structural modeling approaches. As a drawback, KGML-formatted KEGG pathways are primarily designed for visualization purposes and often omit important details for the sake of a clear arrangement of its entries. Thus, a direct conversion into systems biology models would produce incomplete and erroneous models.
resultsHere, we present a precise method for processing and converting KEGG pathways into initial metabolic and signaling models encoded in the standardized community pathway formats SBML (Levels 2 and 3) and BioPAX (Levels 2 and 3). This method involves correcting invalid or incomplete KGML content, creating complete and valid stoichiometric reactions, translating relations to signaling models and augmenting the pathway content with various information, such as cross-references to Entrez Gene, OMIM, UniProt ChEBI, and many more.Finally, we compare several existing conversion tools for KEGG pathways and show that the conversion from KEGG to BioPAX does not involve a loss of information, whilst lossless translations to SBML can only be performed using SBML Level 3, including its recently proposed qualitative models and groups extension packages.
conclusionsBuilding correct BioPAX and SBML signaling models from the KEGG database is a unique characteristic of the proposed method. Further, there is no other approach that is able to appropriately construct metabolic models from KEGG pathways, including correct reactions with stoichiometry. The resulting initial models, which contain valid and comprehensive SBML or BioPAX code and a multitude of cross-references, lay the foundation to facilitate further modeling steps.
Indexed as
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.