Open Access

Computational Methods for Estimation of Cell Cycle Phase Distributions of Yeast Cells

  • Antti Niemistö1Email author,
  • Matti Nykter1,
  • Tommi Aho1,
  • Henna Jalovaara2,
  • Kalle Marjanen1,
  • Miika Ahdesmäki1,
  • Pekka Ruusuvuori1,
  • Mikko Tiainen2,
  • Marja-Leena Linne1 and
  • Olli Yli-Harja1
EURASIP Journal on Bioinformatics and Systems Biology20072007:46150

DOI: 10.1155/2007/46150

Received: 30 June 2006

Accepted: 17 June 2007

Published: 19 August 2007

Abstract

Two computational methods for estimating the cell cycle phase distribution of a budding yeast (Saccharomyces cerevisiae) cell population are presented. The first one is a nonparametric method that is based on the analysis of DNA content in the individual cells of the population. The DNA content is measured with a fluorescence-activated cell sorter (FACS). The second method is based on budding index analysis. An automated image analysis method is presented for the task of detecting the cells and buds. The proposed methods can be used to obtain quantitative information on the cell cycle phase distribution of a budding yeast S. cerevisiae population. They therefore provide a solid basis for obtaining the complementary information needed in deconvolution of gene expression data. As a case study, both methods are tested with data that were obtained in a time series experiment with S. cerevisiae. The details of the time series experiment as well as the image and FACS data obtained in the experiment can be found in the online additional material at http://www.cs.tut.fi/sgn/csb/yeastdistrib/.

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Authors’ Affiliations

(1)
Institute of Signal Processing, Tampere University of Technology
(2)
MediCel Ltd.

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Copyright

© Antti Niemistö et al. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.