Harmonizing semantic annotations for computational models in biology

Abstract

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition, and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current semantic annotation practices among the COmputational Modeling in BIology NEtwork (COMBINE) community and provide a set of recommendations for building a consensus approach to semantic annotation.All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

An updated genome-scale metabolic network reconstruction ofPseudomonas aeruginosaPA14 to characterize mucin-driven shifts in bacterial metabolism

“…All code and data for this project are available on GitHub (github.com/dawsonpayne/iPau21). The genome-scale metabolic model iPau21 is available in the BioModels Database 65 as an SBML Level 3 Version 154 file within a COMBINE Archive OMEX file 66 including the contextualized models and metadata 67 at identifiers.org/biomodels.db/MODEL2106110001.…”

The first 10 years of the international coordination network for standards in systems and synthetic biology (COMBINE)

“…The Center for Reproducible Biomedical Modeling (CRBM, https://reproduciblebiomodels.org/ ), for example, works towards better reproducibility of model-based results in systems biology. In particular, it offers annotation services for composite and harmonised annotations [ 22 ], [ 23 ], technology development to support the modeling workflow, and training. One major roadblock to automated creation of reproducible simulation studies (and annotations) is the lack of appropriate software tools.…”

“…Measuring the quality of annotations and validation of annotations are two difficult tasks to achieve, as measures highly depend on context and application. Ongoing work on harmonising semantic knowledge about computational models was discussed during the meeting [ 23 ], particularly how to realise the next step: going from recommendation to implementation of the OMEX metadata specification.…”

Towards standardization guidelines for in silico approaches in personalized medicine

“…These three ingredients need to be well-documented and each component must be tested for correctness. Reproducibility then requires standard formats to represent the data, detailed descriptions following the Good Scientific Practices described in Minimum Information Guidelines, and semantic annotations [ 8 ], [ 9 ]. The computational biology community has already developed standards for all parts of a typical virtual study and the authors are convinced that these well-established COMBINE standards [ 9 ] shall be thoroughly evaluated for use in predictive in silico models in personalized medicine.…”