Ten simple rules for creating reusable pathway models for computational analysis and visualization

Hanspers, Kristina; Kutmon, Martina; Coort, Susan L.; Digles, Daniela; Dupuis, Lauren J.; Ehrhart, Friederike; Hu, Finterly; Lopes, Élisson Nogueira; Martens, Marvin; Pham, Nhung; Shin, Woosub; Slenter, Denise; Waagmeester, Andra; Willighagen, Egon; Winckers, Laurent; Evelo, Chris T.; Pico, Alexander

doi:10.1371/journal.pcbi.1009226

Cited by 15 publications

(13 citation statements)

References 64 publications

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“…This will preserve the content and ensure its reuse after the map curation is over, for example, for AlzPathway. Active community engagement can lead to establishing consistent guidelines for diagram building, reducing the variability of design choices, and improving the accuracy of compared and shared content (Hanspers et al, 2021 ). Another avenue for development is improvement of the comparison metrics.…”

Section: Discussionmentioning

confidence: 99%

Exploration and comparison of molecular mechanisms across diseases using MINERVA Net

et al. 2023

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Protein function is often interpreted using molecular interaction diagrams, encoding roles a given protein plays in various molecular mechanisms. Information about disease-related mechanisms can be inferred from disease maps, knowledge repositories containing manually constructed systems biology diagrams. Disease maps hosted on the Molecular Interaction Network VisuAlization (MINERVA) Platform are individually accessible through a REST API interface of each instance, making it challenging to systematically explore their contents. To address this challenge, we introduce the MINERVA Net web service, a repository of open-access disease maps allowing users to publicly share minimal information about their maps. The MINERVA Net repository provides REST API endpoints of particular disease maps, which then can be individually queried for content. In this article, we describe the concept of MINERVA Net and illustrate its use by comparing proteins and their interactions in three different disease maps.

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Section: Discussionmentioning

confidence: 99%

Exploration and comparison of molecular mechanisms across diseases using MINERVA Net

et al. 2023

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“…For the actual drawing of the pathways we followed the curation guidelines described on the WikiPathways website [https://www.WikiPathways.org/index.php/Help:Guidelines], and the advice for pathway drawing given in the 10 simple rules paper by Hanspers et al (2021) (30). Based on that Molecular Interaction Map interactions (31) were for standard interaction types like 'stimulation' and 'conversion', interactions not captured in these such as exocytosis and transportation were drawn using unspeci ed basic interaction types.…”

Section: Curation Of Pathwaysmentioning

confidence: 99%

Interactive neuroinflammation pathways and transcriptomics-based identification of drugs and chemical compounds for schizophrenia

Koole

Martinez

Amelsvoort

et al. 2022

Preprint

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Background Schizophrenia is a psychiatric disorder affecting one percent of the worldwide population. Despite the progress in elucidating its aetiology, treatment strategies have not succeeded in alleviating the symptoms effectively. Accumulating evidence indicates that neuroinflammation is involved in the pathology of these disorders by altering neurodevelopmental processes and specifically affecting glutamatergic signalling and astrocytic functioning. Omics data analysis can facilitate the assessment of these mechanisms and help to identify new therapeutic strategies. The aim of this study was to curate and publish interactive biological pathways involved in schizophrenia for the identification of novel pharmacological targets implementing pathway, gene ontology, and network enrichment analysis. Methods Neuroinflammatory pathways were created using PathVisio and published in WikiPathways. A transcriptomics dataset, originally created by Narla et al. was selected for data visualisation and analysis. Gene ontology terms and pathways were obtained for differentially expressed genes using g:Profiler and BiNGO. Transcriptomics data was visualised within the curated pathways. Cytoscape was used for network-based gene set and pathway enrichment analyses. Networks were extended with transcription factors, pathways, and drugs and then network hubs were determined based on degrees of connectivity. Results Glutamatergic, immune, and astrocytic signalling as well as extracellular matrix reorganisation were altered in schizophrenia while we did not find an effect on the complement system. The alterations might impair neural development and maintenance. Transcription factor networks revealed complex interactions between transcription factors, transporters, and inflammatory receptors. We also report pharmacological agents that target the glutamate receptor subunits, inflammatory mediators, and metabolic enzymes found. Conclusion New neuroinflammatory pathways incorporating the extracellular matrix, glutamatergic neurons, and astrocytes in the aetiology of schizophrenia were established. Transcriptomics based network analysis provided novel targets, including extra-synaptic glutamate receptors, glutamate transporters and extracellular matrix molecules that can be evaluated for therapeutic strategies.

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“…way construction [7] offer valuable introductory material for constructing disease-oriented resources. In particular, an article on construction of a Reactome-based specific knowledge repository [8] proposes instructions on reuse of pathway diagrams in a specific context.…”

Section: Of 19mentioning

confidence: 99%

“…Other useful sources on the topic of annotation are the recommendations of the logical modelling community [40], the Reactome data model and pathway development practices [8], the rules suggested for creating reusable pathway models [7], the documentation of the MI2CAST format (Minimum Information about a Molecular Interaction CAusal STatement) [56] and the protocol for high-quality metabolic reconstruction [57].…”

Section: Different Types Of Map Entities Are Shown Inmentioning

confidence: 99%

High-quality Reconstruction of Disease Mechanisms: Planning, Development and Maintenance

Mazein¹,

Acencio²,

Balaur³

et al. 2022

Preprint

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As a conceptual model of disease mechanisms, a disease map integrates available knowledge and is applied for data interpretation, predictions and hypothesis generation. It is possible to model disease mechanisms on different levels of granularity and adjust the approach to the goals of a particular project. This rich environment together with requirements for high-quality network reconstruction makes it challenging for new curators and groups to be quickly introduced to the development methods. In this review, we offer a step-by-step guide for developing a disease map within its mainstream pipeline that involves using the CellDesigner tool for creating and editing diagrams and the MINERVA Platform for online visualisation and exploration. We also describe how the Neo4j graph database environment can be used for managing and querying efficiently such a resource. For assessing the interoperability and reproducibility we apply FAIR principles.

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Ten simple rules for creating reusable pathway models for computational analysis and visualization

Cited by 15 publications

References 64 publications

Exploration and comparison of molecular mechanisms across diseases using MINERVA Net

Exploration and comparison of molecular mechanisms across diseases using MINERVA Net

Interactive neuroinflammation pathways and transcriptomics-based identification of drugs and chemical compounds for schizophrenia

High-quality Reconstruction of Disease Mechanisms: Planning, Development and Maintenance

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