A computational statistics approach for estimating the spatial range of morphogen gradients

Jitendra S. Kanodia, Yoosik Kim, Raju Tomer, Zia Khan, Kwanghun Chung, John D. Storey, Hang Lu, Philipp J. Keller, Stanislav Y. Shvartsman

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)4867-4874
Number of pages8
JournalDevelopment
Volume138
Issue number22
DOIs
Publication statusPublished - 2011 Nov 15

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Developmental Biology

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  • Cite this

    Kanodia, J. S., Kim, Y., Tomer, R., Khan, Z., Chung, K., Storey, J. D., Lu, H., Keller, P. J., & Shvartsman, S. Y. (2011). A computational statistics approach for estimating the spatial range of morphogen gradients. Development, 138(22), 4867-4874. https://doi.org/10.1242/dev.071571