Abstract
We review studies on tissue transplantation experiments for various species: one piece of the donor tissue is excised and transplanted into a slit in the host tissue, then observe the behavior of this grafted tissue. Although we have known the results of some transplantation experiments, there are many more possible experiments with unknown results. We develop a penalty function-based method that uses the known experimental results to infer the unknown experimental results. Similar experiments without similar results get penalized and correspond to smaller probability. This method can provide the most probable results of a group of experiments or the probability of a specific result for each experiment. This method is also generalized to other situations. Besides, we solve a problem: how to design experiments so that such a method can be applied most efficiently.
Original language | English (US) |
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Article number | 110645 |
Journal | Journal of Theoretical Biology |
Volume | 520 |
DOIs | |
State | Published - Jul 7 2021 |
All Science Journal Classification (ASJC) codes
- Agricultural and Biological Sciences(all)
- Applied Mathematics
- Biochemistry, Genetics and Molecular Biology(all)
- Immunology and Microbiology(all)
- Statistics and Probability
- Modeling and Simulation
Keywords
- Experimental design
- Experimental result inference
- Penalty function
- Similarity between experiments