What’s next for computational systems biology? Article Swipe
Eberhard O. Voit
,
Ashti M. Shah
,
Daniel V. Olivença
,
Yoram Vodovotz
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/fsysb.2023.1250228
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/fsysb.2023.1250228
Largely unknown just a few decades ago, computational systems biology is now a central methodology for biological and medical research. This amazing ascent raises the question of what the community should do next. The article outlines our personal vision for the future of computational systems biology, suggesting the need to address both mindsets and methodologies. We present this vision by focusing on current and anticipated research goals, the development of strong computational tools, likely prominent applications, education of the next-generation of scientists, and outreach to the public. In our opinion, two classes of broad research goals have emerged in recent years and will guide future efforts. The first goal targets computational models of increasing size and complexity, aimed at solving emerging health-related challenges, such as realistic whole-cell and organ models, disease simulators and digital twins, in silico clinical trials, and clinically translational applications in the context of therapeutic drug development. Such large models will also lead us toward solutions to pressing issues in agriculture and environmental sustainability, including sufficient food availability and life in changing habitats. The second goal is a deep understanding of the essence of system designs and strategies with which nature solves problems. This understanding will help us explain observed biological structures and guide forays into synthetic biological systems. Regarding effective methodologies, we suggest efforts toward automated data pipelines from raw biomedical data all the way to spatiotemporal mechanistic model. These will be supported by dynamic methods of statistics, machine learning, artificial intelligence and streamlined strategies of dynamic model design, striking a fine balance between modeling realistic complexity and abstracted simplicity. Finally, we suggest the need for a concerted, community-wide emphasis on effective education in systems biology, implemented as a combination of formal instruction and hands-on mentoring. The educational efforts should furthermore be extended toward the public through books, blogs, social media, and interactive networking opportunities, with the ultimate goal of training in state-of-the-art technology while recapturing the lost art of synthesis.
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Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.3389/fsysb.2023.1250228
- https://www.frontiersin.org/articles/10.3389/fsysb.2023.1250228/pdf?isPublishedV2=False
- OA Status
- diamond
- Cited By
- 7
- References
- 168
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386894015
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4386894015Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/fsysb.2023.1250228Digital Object Identifier
- Title
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What’s next for computational systems biology?Work title
- Type
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reviewOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-09-19Full publication date if available
- Authors
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Eberhard O. Voit, Ashti M. Shah, Daniel V. Olivença, Yoram VodovotzList of authors in order
- Landing page
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https://doi.org/10.3389/fsysb.2023.1250228Publisher landing page
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https://www.frontiersin.org/articles/10.3389/fsysb.2023.1250228/pdf?isPublishedV2=FalseDirect link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://www.frontiersin.org/articles/10.3389/fsysb.2023.1250228/pdf?isPublishedV2=FalseDirect OA link when available
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Data science, Context (archaeology), Computer science, Computational model, Management science, Outreach, Artificial intelligence, Risk analysis (engineering), Engineering, Biology, Medicine, Political science, Law, PaleontologyTop concepts (fields/topics) attached by OpenAlex
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7Total citation count in OpenAlex
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2025: 3, 2024: 4Per-year citation counts (last 5 years)
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168Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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