TY - JOUR
T1 - Quantitative Models of Developmental Pattern Formation
AU - Reeves, Gregory T.
AU - Muratov, Cyrill B.
AU - Schüpbach, Trudi
AU - Shvartsman, Stanislav Y.
N1 - Funding Information:
The authors thank Jeff Axelrod, Tatiana Belenkaya, Chris Bristow, Mathieu Coppey, Ian Dworkin, Matthew Gibson, Lea Goentoro, Arthur Lander, Jessica Lembong, Xinhua Lin, Dmitry Papatsenko, Claire Tomlin, David Umulis, Nir Yakoby, and Jeremy Zartman for helpful discussions. We are grateful to Jeff Axelrod, Dmitry Papatsenko, Mike Levine, Xinhua Lin, and L.S. Shashidhara for providing the images. G.T.R. has been supported by the NSF graduate research fellowship and the Princeton University Wu Fellowship. C.B.M. has been partially supported by NIH grant R01 GM076690. T.S. was partially supported by the Howard Hughes Medical Institute and by NIH grant P01 CA41086. S.Y.S. has been partially supported by grants from the Searle Family, AP Sloan Foundation, Dreyfus Foundation, NIH grant R01 GM076690, and the NSF Career Award.
PY - 2006/9
Y1 - 2006/9
N2 - Pattern formation in developing organisms can be regulated at a variety of levels, from gene sequence to anatomy. At this level of complexity, mechanistic models of development become essential for integrating data, guiding future experiments, and predicting the effects of genetic and physical perturbations. However, the formulation and analysis of quantitative models of development are limited by high levels of uncertainty in experimental measurements, a large number of both known and unknown system components, and the multiscale nature of development. At the same time, an expanding arsenal of experimental tools can constrain models and directly test their predictions, making the modeling efforts not only necessary, but feasible. Using a number of problems in fruit fly development, we discuss how models can be used to test the feasibility of proposed patterning mechanisms and characterize their systems-level properties.
AB - Pattern formation in developing organisms can be regulated at a variety of levels, from gene sequence to anatomy. At this level of complexity, mechanistic models of development become essential for integrating data, guiding future experiments, and predicting the effects of genetic and physical perturbations. However, the formulation and analysis of quantitative models of development are limited by high levels of uncertainty in experimental measurements, a large number of both known and unknown system components, and the multiscale nature of development. At the same time, an expanding arsenal of experimental tools can constrain models and directly test their predictions, making the modeling efforts not only necessary, but feasible. Using a number of problems in fruit fly development, we discuss how models can be used to test the feasibility of proposed patterning mechanisms and characterize their systems-level properties.
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U2 - 10.1016/j.devcel.2006.08.006
DO - 10.1016/j.devcel.2006.08.006
M3 - Review article
C2 - 16950121
AN - SCOPUS:33747871080
SN - 1534-5807
VL - 11
SP - 289
EP - 300
JO - Developmental Cell
JF - Developmental Cell
IS - 3
ER -