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

doi:10.1242/dev.071571

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

Yonsei Advanced Science Institute

Research output: Contribution to journal › Article › peer-review

24 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 language	English
Pages (from-to)	4867-4874
Number of pages	8
Journal	Development
Volume	138
Issue number	22
DOIs	https://doi.org/10.1242/dev.071571
Publication status	Published - 2011 Nov 15

All Science Journal Classification (ASJC) codes

Molecular Biology
Developmental Biology

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10.1242/dev.071571

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AU - Tomer, Raju

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AU - Chung, Kwanghun

AU - Storey, John D.

AU - Lu, Hang

AU - Keller, Philipp J.

AU - Shvartsman, Stanislav Y.

PY - 2011/11/15

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

Abstract

All Science Journal Classification (ASJC) codes

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