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Related Experiment Video

Updated: Jun 19, 2026

3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse
15:26

3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse

Published on: May 19, 2015

From spatial-data to 3D models of the developing human brain.

Xunxian Wang1, Susan Lindsay, Richard Baldock

  • 1Institute of Human Genetics, Newcastle University, UK. xunxian.wang@ncl.ac.uk

Methods (San Diego, Calif.)
|October 6, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces software for reconstructing 3D gene expression domains in early human brain development. It interpolates sparse 2D data to map gene patterns in developing tissues.

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Area of Science:

  • Developmental Biology
  • Computational Biology
  • Genomics

Background:

  • Gene expression data is vital for understanding early brain development.
  • Spatial data provides multi-level insights into developmental processes.
  • Generating 3D spatial gene expression data for early human fetal stages is challenging due to tissue limitations.

Purpose of the Study:

  • To develop software for reconstructing 3D gene expression domains from sparse 2D data.
  • To facilitate the analysis of gene expression patterns during human fetal brain development.
  • To address limitations in time and space sampling of gene expression data.

Main Methods:

  • Software developed for reconstructing 3D domains by interpolating sparse 2D gene expression patterns.
  • Mapping 2D patterns to 3D models of human developmental stages.
  • Utilizing procedures including component clustering, tracking, shape matching, and point interpolation.

Main Results:

  • Demonstrated software capability to reconstruct 3D gene expression domains.
  • Successfully inferred expression domains in gaps using proposed procedures.
  • Provided results on exemplar gene data, validating the approach.

Conclusions:

  • The developed software enables 3D reconstruction of gene expression domains from limited spatial data.
  • This approach enhances the study of gene expression during early human brain development.
  • The software offers a valuable tool for computational biology and developmental genomics research.