WikiPathways: Pathway Editing for the People

Pico, Alexander R.; Kelder, Thomas; Iersel, Martijn P. van; Hanspers, Kristina; Conklin, Bruce R.; Evelo, Chris T.

doi:10.1371/journal.pbio.0060184

Cited by 590 publications

(508 citation statements)

References 12 publications

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“…To make sense of the 154 dependency genes, we first grouped the hits into well-defined functional categories, using a combination of the Reactome (Croft et al, 2011), KEGG Petrocca et al, 2/2/16, page 7 (Kanehisa et al, 2010) and Wikipathway (Pico et al, 2008) databases (Tables S3 and S4). Of the 154 genes, 121 had well described annotations that could be grouped into 13 functions with at least 3 assigned genes.…”

Section: Bpler Dependency Genes Cluster Within Defined Functional Catmentioning

confidence: 99%

miR-200 promotes the mesenchymal to epithelial transition by suppressing multiple members of the Zeb2 and Snail1 transcriptional repressor complexes

et al. 2015

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Section: Bpler Dependency Genes Cluster Within Defined Functional Catmentioning

confidence: 99%

miR-200 promotes the mesenchymal to epithelial transition by suppressing multiple members of the Zeb2 and Snail1 transcriptional repressor complexes

et al. 2015

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“…Such curated pathways could subsequently be re-collated into the reconstruction, which would then be formatted and reanalysed, following the iterative cycle described above. Such crowd-sourcing methods are already exploited in the web-based curation of individual pathways [40,41] and would prove useful in the iterative development of larger-scale networks. The recently developed software MEMOSys [42] may support such an approach, providing a secure web-enabled interface for community driven, multi-user development and refinement of reconstructions.…”

Section: Discussionmentioning

confidence: 99%

The SuBliMinaL Toolbox: automating steps in the reconstruction of metabolic networks

Swainston

Smallbone

Mendes

et al. 2011

Journal of Integrative Bioinformatics

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Summary The generation and use of metabolic network reconstructions has increased over recent years. The development of such reconstructions has typically involved a time-consuming, manual process. Recent work has shown that steps undertaken in reconstructing such metabolic networks are amenable to automation. The SuBliMinaL Toolbox (http://www.mcisb.org/subliminal/) facilitates the reconstruction process by providing a number of independent modules to perform common tasks, such as generating draft reconstructions, determining metabolite protonation state, mass and charge balancing reactions, suggesting intracellular compartmentalisation, adding transport reactions and a biomass function, and formatting the reconstruction to be used in third-party analysis packages. The individual modules manipulate reconstructions encoded in Systems Biology Markup Language (SBML), and can be chained to generate a reconstruction pipeline, or used individually during a manual curation process. This work describes the individual modules themselves, and a study in which the modules were used to develop a metabolic reconstruction of Saccharomyces cerevisiae from the existing data resources KEGG and MetaCyc. The automatically generated reconstruction is analysed for blocked reactions, and suggestions for future improvements to the toolbox are discussed.

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“…The Nutrigenomics Organization has begun the development of a nutritional phenotype database (dbNP- [64]), a research and collaboration tool, and knowledge base which will allow access to publically available data. A separate yet key component of dbNP is WikiPathways [36,48], an open, collaborative platform for the curation of biological pathways (http:// www.wikipathways.org) based on all data available to the curator.…”

Section: Databasesmentioning

confidence: 99%

Connecting the Human Variome Project to nutrigenomics

et al. 2010

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Nutrigenomics is the science of analyzing and understanding gene-nutrient interactions, which because of the genetic heterogeneity, varying degrees of interaction among gene products, and the environmental diversity is a complex science. Although much knowledge of human diversity has been accumulated, estimates suggest that *90% of genetic variation has not yet been characterized. Identification of the DNA sequence variants that contribute to nutrition-related disease risk is essential for developing a better understanding of the complex causes of disease in humans, including nutrition-related disease. The Human Variome Project (HVP; http://www.humanvariomeproject. org/) is an international effort to systematically identify genes, their mutations, and their variants associated with phenotypic variability and indications of human disease or phenotype. Since nutrigenomic research uses genetic information in the design and analysis of experiments, the HVP is an essential collaborator for ongoing studies of gene-nutrient interactions. With the advent of next generation sequencing methodologies and the understanding of the undiscovered variation in human genomes, the nutrigenomic community will be generating novel sequence data and results. The guidelines and practices of the HVP can guide and harmonize these efforts.

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WikiPathways: Pathway Editing for the People

Abstract: WikiPathways provides a collaborative platform for creating, updating, and sharing pathway diagrams and serves as an example of content curation by the biology community.

Cited by 590 publications

References 12 publications

miR-200 promotes the mesenchymal to epithelial transition by suppressing multiple members of the Zeb2 and Snail1 transcriptional repressor complexes

miR-200 promotes the mesenchymal to epithelial transition by suppressing multiple members of the Zeb2 and Snail1 transcriptional repressor complexes

The SuBliMinaL Toolbox: automating steps in the reconstruction of metabolic networks

Connecting the Human Variome Project to nutrigenomics

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