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Abstract BackgroundAt the molecular level, nonlinear networks of heterogeneous molecules control many biological processes, so that systems biology provides a valuable approach in this field, building on the integration of experimental biology with mathematical modeling. One of the biggest challenges to making this integration a reality is that many life scientists do not possess the mathematical expertise needed to build and manipulate mathematical models well enough to use them as tools for hypothesis generation. Available modeling software packages often assume some modeling expertise. There is a need for software tools that are easy to use and intuitive for experimentalists. ResultsThis paper introduces PlantSimLab, a web-based application developed to allow plant biologists to construct dynamic mathematical models of molecular networks, interrogate them in a manner similar to what is done in the laboratory, and use them as a tool for biological hypothesis generation. It is designed to be used by experimentalists, without direct assistance from mathematical modelers. ConclusionsMathematical modeling techniques are a useful tool for analyzing complex biological systems, and there is a need for accessible, efficient analysis tools within the biological community. PlantSimLab enables users to build, validate, and use intuitive qualitative dynamic computer models, with a graphical user interface that does not require mathematical modeling expertise. It makes analysis of complex models accessible to a larger community, as it is platform-independent and does not require extensive mathematical expertise.
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Imagine It! Choose Your Own Pattern Block Adventure
When given the opportunity to play with mathematical materials and ideas, children demonstrate their mathematical understanding in innovative ways.
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- Award ID(s):
- 2101356
- PAR ID:
- 10533895
- Publisher / Repository:
- NCTM
- Date Published:
- Journal Name:
- Mathematics Teacher: Learning and Teaching PK-12
- Volume:
- 116
- Issue:
- 10
- ISSN:
- 0025-5769
- Page Range / eLocation ID:
- 737 to 745
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript
- Journal Article:
- https://doi.org/10.5951/MTLT.2023.0064
