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Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units.
57 pages
570, Science, FOS: Physical sciences, Bioengineering, 3101 Biochemistry and Cell Biology, Quantitative Biology - Quantitative Methods, Models, Biological, Fluorescence, Theoretical, Models, Computer Simulation, Physics - Biological Physics, anzsrc-for: 31 Biological Sciences, anzsrc-for: 51 Physical Sciences, Quantitative Methods (q-bio.QM), Microscopy, Photons, 000, anzsrc-for: 3101 Biochemistry and Cell Biology, Q, R, Models, Theoretical, Biological, 1.5 Resources and infrastructure (underpinning), Networking and Information Technology R&D (NITRD), Microscopy, Fluorescence, Biological Physics (physics.bio-ph), FOS: Biological sciences, Medicine, Generic health relevance, 51 Physical Sciences, 31 Biological Sciences, Physics - Optics, Research Article, Optics (physics.optics)
570, Science, FOS: Physical sciences, Bioengineering, 3101 Biochemistry and Cell Biology, Quantitative Biology - Quantitative Methods, Models, Biological, Fluorescence, Theoretical, Models, Computer Simulation, Physics - Biological Physics, anzsrc-for: 31 Biological Sciences, anzsrc-for: 51 Physical Sciences, Quantitative Methods (q-bio.QM), Microscopy, Photons, 000, anzsrc-for: 3101 Biochemistry and Cell Biology, Q, R, Models, Theoretical, Biological, 1.5 Resources and infrastructure (underpinning), Networking and Information Technology R&D (NITRD), Microscopy, Fluorescence, Biological Physics (physics.bio-ph), FOS: Biological sciences, Medicine, Generic health relevance, 51 Physical Sciences, 31 Biological Sciences, Physics - Optics, Research Article, Optics (physics.optics)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 12 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |