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SCMD: Saccharomyces cerevisiae Morphological Database.

Taro L Saito1, Miwaka Ohtani, Hiroshi Sawai

  • 1Department of Computer Science, Graduate School of Information Science and Technology, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.

Nucleic Acids Research
|December 19, 2003
PubMed
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Researchers developed automated image-processing software to analyze yeast cell morphology, creating the Saccharomyces cerevisiae Morphological Database (SCMD) for global regulation studies.

Area of Science:

  • Cell Biology
  • Bioinformatics
  • Genomics

Background:

  • Manual analysis of yeast cell morphology is time-consuming and subjective.
  • Genome-wide screening data for yeast mutants with abnormal morphology is increasingly available.
  • Understanding cell morphology regulation is crucial in cell biology.

Purpose of the Study:

  • To develop automated image-processing software for yeast cell morphology analysis.
  • To create a comprehensive database of yeast cell morphology data.
  • To facilitate the analysis of abnormal yeast cells and identify mutants with similar morphological traits.

Main Methods:

  • Developed image-processing software to automatically extract and measure yeast cells from micrographs.
  • Quantitatively analyzed cell size, roundness, bud neck position angle, nuclear DNA, and actin localization.

Related Experiment Videos

  • Compiled data from 2531 mutants, encompassing 960,609 cells and 52,988 micrographs.

    • Main Results:

    • Successfully retrieved and processed a large-scale dataset of yeast cell morphology.
    • Established the Saccharomyces cerevisiae Morphological Database (SCMD) with quantitative morphological data.
    • Implemented a system for ranking mutants by similarity of average morphological parameters.

    Conclusions:

    • The developed software and SCMD provide objective, quantitative data for yeast cell morphology.
    • The SCMD facilitates global regulation studies of cell morphology by enabling efficient analysis of mutant phenotypes.
    • Automated analysis significantly improves the efficiency and objectivity of cell morphology research.