Conceptual modelling for life sciences based on systemist foundations

Background All aspects of our society, including the life sciences, need a mechanism for people working within them to represent the concepts they employ to carry out their research. For the information systems being designed and developed to support researchers and scientists in conducting their wo...

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Bibliographic Details
Published in:BMC bioinformatics Vol. 23; no. Suppl 11; pp. 574 - 27
Main Authors: Lukyanenko, Roman, Storey, Veda C., Pastor, Oscar
Format: Journal Article
Language:English
Published: London BioMed Central 13.06.2023
BioMed Central Ltd
Springer Nature B.V
BMC
Subjects:
Algorithms
Analysis
Bioinformatics
Biomedical and Life Sciences
Chaos theory
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Computer simulation
Computer-generated environments
Conceptual modelling
Domains
Foundations
Genomes
Information systems
Life Sciences
Methods
Microarrays
Modelling
Precision medicine
Problem solving
Scientists
Semantics
System composition diagram
Systemist perspective
Systems
Systems development
Systems modelling
Systems theory
Well being
United States
System composition diagram
Life sciences
Conceptual modelling
Systemist perspective
Systems modelling
Systems
ISSN:1471-2105, 1471-2105
Online Access:Get full text
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Summary:Background All aspects of our society, including the life sciences, need a mechanism for people working within them to represent the concepts they employ to carry out their research. For the information systems being designed and developed to support researchers and scientists in conducting their work, conceptual models of the relevant domains are usually designed as both blueprints for a system being developed and as a means of communication between the designer and developer. Most conceptual modelling concepts are generic in the sense that they are applied with the same understanding across many applications. Problems in the life sciences, however, are especially complex and important, because they deal with humans, their well-being, and their interactions with the environment as well as other organisms. Results This work proposes a “systemist” perspective for creating a conceptual model of a life scientist’s problem. We introduce the notion of a system and then show how it can be applied to the development of an information system for handling genomic-related information. We extend our discussion to show how the proposed systemist perspective can support the modelling of precision medicine. Conclusion This research recognizes challenges in life sciences research of how to model problems to better represent the connections between physical and digital worlds. We propose a new notation that explicitly incorporates systemist thinking, as well as the components of systems based on recent ontological foundations. The new notation captures important semantics in the domain of life sciences. It may be used to facilitate understanding, communication and problem-solving more broadly. We also provide a precise, sound, ontologically supported characterization of the term “system,” as a basic construct for conceptual modelling in life sciences.
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ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-023-05287-z