Published June 16, 2021 | Version v1

Dataset supporting the manuscript dedicated to lignin precursor incorporation analysis, bioorthogonal labeling, parametric and AI based segmentation.

  • 1. Univ. Lille, CNRS, UMR 8576 – UGSF - Unité de Glycobiologie Structurale et Fonctionnelle, F 59000 Lille, France Department of Nanobiotechnology (DNBT), Institute for Biophysics, University of Natural Resources and Life Sciences (BOKU), Muthgasse 11-II, 1190, Vienna, Austria
  • 2. Univ. Lille, CNRS, UMR 8576 – UGSF - Unité de Glycobiologie Structurale et Fonctionnelle, F 59000 Lille, France
  • 3. Univ. Lille, CNRS, UMR 8576 – UGSF - Unité de Glycobiologie Structurale et Fonctionnelle, F 59000 Lille, France Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, US 41 - UMS 2014 - PLBS, F-59000 Lille, France
  • 4. Department of Nanobiotechnology (DNBT), Institute for Biophysics, University of Natural Resources and Life Sciences (BOKU), Muthgasse 11-II, 1190, Vienna, Austria

Description

This dataset aims to test the algorithms presented in an article submitted by the authors and untitled:

The combination of chemical reporter-, segmentation- and ratiometric-methods enables high-quality mapping of lignification dynamics in plant cell walls

Are available:

-the algorithm with graphical user interface for imageJ and its installation procedure ("Cell_Wall_Segmentation " and "Tutorial Cell_Wall_Segmentation")

-a folder comprising a classifier and a data set compatible with the machine learning part of the algorithm "data and classifier for weka"

- representative images adapted for testing “representative images”

- the macro corresponding to the parametric segmentation procedure (see imageJ documentation for installation instructions) “parametric_segmentation”

Files

Cell_Wall_Segmentation.zip

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