|Title||A computational statistics approach for estimating the spatial range of morphogen gradients.|
|Publication Type||Journal Article|
|Year of Publication||2011|
|Authors||Kanodia, JS, Kim, Y, Tomer, R, Khan, Z, Chung, K, Storey, JD, Lu, H, Keller, PJ, Shvartsman, SY|
|Date Published||2011 Nov|
|Keywords||Animals, Biostatistics, Cleavage Stage, Ovum, Computational Biology, Computer Simulation, Drosophila, Drosophila Proteins, Embryo, Nonmammalian, Gene Expression Regulation, Developmental, Genes, Developmental, Imaging, Three-Dimensional, In Situ Hybridization, Fluorescence, Morphogenesis, Osmolar Concentration, Tissue Distribution|
A crucial issue in studies of morphogen gradients relates to their range: the distance over which they can act as direct regulators of cell signaling, gene expression and cell differentiation. To address this, we present a straightforward statistical framework that can be used in multiple developmental systems. We illustrate the developed approach by providing a point estimate and confidence interval for the spatial range of the graded distribution of nuclear Dorsal, a transcription factor that controls the dorsoventral pattern of the Drosophila embryo.