## Analysis Techniques for Microarray Time-Series Data (Extended Abstract) (2000)

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Venue: | J. Comput. Biol |

Citations: | 54 - 2 self |

### BibTeX

@ARTICLE{Filkov00analysistechniques,

author = {Vladimir Filkov and Steven Skiena and Jizu Zhi},

title = {Analysis Techniques for Microarray Time-Series Data (Extended Abstract)},

journal = {J. Comput. Biol},

year = {2000},

volume = {9},

pages = {317--330}

}

### Years of Citing Articles

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### Abstract

Vladimir Filkov Steven Skiena Jizu Zhi Dept. of Computer Science and Center for Biotechnology State University of New York Stony Brook, NY 11794-4400 fvl lkov|skiena|zjizug@cs.sunysb.edu September 27, 2000 1

### Citations

2091 |
Cluster analysis and display of genome-wide expression patterns
- Eisen, Spellman, et al.
- 1998
(Show Context)
Citation Context ... cell cycle regulation. The importance of the Cho and Spellman data sets is perhaps best revealed by the variety of methodologies being applied to analyze it. Clustering studies and promoter analysis =-=[5, 12]-=- have been used to classify genes according to where they are active in the cell cycle. We [2] have developed a system for proposing putative gene regulatory networks by identifying activators and inh... |

798 | D (2000) Using Bayesian networks to analyze expression data
- Friedman, Linial, et al.
(Show Context)
Citation Context ...l cycle. We [2] have developed a system for proposing putative gene regulatory networks by identifying activators and inhibitors using signal processing and combinatorial optimization. Friedman et.al =-=[7-=-] have built a system similar in spirit analyzing the same data, but based instead on Bayesian networks. Techniques for analyzing these data sets using dierential equation modeling [3], wavelets [10],... |

419 |
Singular value decomposition for genome-wide expression data processing and modeling
- Alter
- 2000
(Show Context)
Citation Context ... York, Stony Brook, NY 11794. 2 Center for Biotechnology, State University of New York, Stony Brook, NY 11794. 317s318 FILKOV ET AL. (Klevecz and Dowse, 2000), and singular value decomposition (SVD) (=-=Alter et al., 2000-=-; Holter et al., 2000) have also been explored. In general, this analysis has succeeded in revealing certain gross periodicities in the data corresponding to the cell and other cycles and has generate... |

383 |
A genome-wide transcriptional analysis of the mitotic cell cycle. Mol. Cell 2:65–73
- Cho, Campbell, et al.
- 1998
(Show Context)
Citation Context ...s of time-series data on gene expression in a particular organism under various conditions. Extensive time-series data on gene expression in yeast (Saccharomyces cerevisiae) have been obtained by Cho =-=[4]-=- and Spellman [12] using microarrays, greatly expanding our knowledge of which genes involved in cell cycle regulation. The importance of the Cho and Spellman data sets is perhaps best revealed by the... |

187 | Modeling gene expression with differential equations
- Chen, He, et al.
- 1999
(Show Context)
Citation Context ... applied to analyze it. Clustering studies and promoter analysis (Eisen et al., 1998; Spellman et al., 1998) have been used to classify genes according to where they are active in the cell cycle. We (=-=Chen et al., 1999-=-a) have developed a system for proposing putative gene regulatory networks by identifying activators and inhibitors using signal processing and combinatorial optimization. Friedman et al. (2000) have ... |

101 | Aligning gene expression time series with time warping algorithms - Aach, Church |

94 |
Fundamental patterns underlying gene expression profiles: Simplicity from complexity
- Holter, Mitra, et al.
- 2000
(Show Context)
Citation Context ...nalyzing the same data, but based instead on Bayesian networks. Techniques for analyzing these data sets using dierential equation modeling [3], wavelets [10], and singular value decomposition (SVD) [=-=9]-=- have also been explored. In general, this analysis has succeeded in revealing certain gross periodicities in the data corresponding to the cell and other cycles, and generated untested predictions of... |

54 |
Statistical methods. The Iowa State
- Snedecor
- 1956
(Show Context)
Citation Context ... of dierent lengths. Statistically, Figure 2 gives the distributions of the correlation coecient for various lengths. Finding analytical forms for these distributions is known to be a dicult problem [=-=11-=-]. The results of Figure 2 can be use correct the plots of Figure 1(a) in comparing correlations of dierent length cycle windows. Corrected plots are provided in Figure 1(b), clearly dampen or elimina... |

48 | Identifying Gene Regulatory Networks from Experimental Data
- Chen, Filkov, et al.
(Show Context)
Citation Context ...by the variety of methodologies being applied to analyze it. Clustering studies and promoter analysis [5, 12] have been used to classify genes according to where they are active in the cell cycle. We =-=[2]-=- have developed a system for proposing putative gene regulatory networks by identifying activators and inhibitors using signal processing and combinatorial optimization. Friedman et.al [7] have built ... |

27 |
Molecular classi of cancer: class discovery and class prediction by gene expression monitoring
- Golub, Slonim, et al.
- 1999
(Show Context)
Citation Context ... sampled for one period, and only coarsely at that. Microarray data has also been used to distinguish between tissue types, providing new methods for diagnosing dierent types of cancers and leukemia [=-=1, 8]-=-. These data sets compare expression in two distinct cell populations, and typically do not represent time-series courses. 3 Integrating Cell Cycle Data Sets We sought to interleave all four of the Ch... |

20 |
Comprehensive Identi cation of cell cycle-regulated genes of the yeast saccharomyces cerevisiae by microarray hybridization
- Spellman, Zhang, et al.
- 1998
(Show Context)
Citation Context ...ression in a particular organism under various conditions. Extensive time-series data on gene expression in yeast (Saccharomyces cerevisiae) have been obtained by Cho (Cho et al., 1998) and Spellman (=-=Spellman et al., 1998-=-) using microarrays, greatly expanding our knowledge of which genes are involved in cell cycle regulation. The importance of the Cho and Spellman data sets is perhaps best revealed by the variety of m... |

14 |
Comprehensive identi of cell cycle-regulated genes of the yeast saccharomyces cerevisiae by microarray hybridization
- Spellman, Sherlock, et al.
- 1998
(Show Context)
Citation Context ...data on gene expression in a particular organism under various conditions. Extensive time-series data on gene expression in yeast (Saccharomyces cerevisiae) have been obtained by Cho [4] and Spellman =-=[12]-=- using microarrays, greatly expanding our knowledge of which genes involved in cell cycle regulation. The importance of the Cho and Spellman data sets is perhaps best revealed by the variety of method... |

10 |
2000, `Tissue Classi with Gene Expression Pro
- Ben-Dor, Bruhn, et al.
(Show Context)
Citation Context ... sampled for one period, and only coarsely at that. Microarray data has also been used to distinguish between tissue types, providing new methods for diagnosing dierent types of cancers and leukemia [=-=1, 8]-=-. These data sets compare expression in two distinct cell populations, and typically do not represent time-series courses. 3 Integrating Cell Cycle Data Sets We sought to interleave all four of the Ch... |

3 | Modeling gene expression with di erential equations - Chen, He, et al. - 1999 |

3 |
Tuning in the transcriptome: Basins of attraction in the yeast cell cycle
- Klevecz, Dowse
- 2000
(Show Context)
Citation Context ...l [7] have built a system similar in spirit analyzing the same data, but based instead on Bayesian networks. Techniques for analyzing these data sets using dierential equation modeling [3], wavelets [=-=10]-=-, and singular value decomposition (SVD) [9] have also been explored. In general, this analysis has succeeded in revealing certain gross periodicities in the data corresponding to the cell and other c... |

1 | Covering points on a circle with circular arcs
- Filkov
- 2000
(Show Context)
Citation Context ... data sets. Instead, we explored how well discrete similarity methods can work, which we used for analyzing short sequences in [2]. We have previously explored geometric approaches to cycle detection =-=[6]. Our-=- main idea is as follows. Consider a periodic time-series curve with more than one period. The similarity of a \window" (i.e. a sub-range of the time-series function) with the same-length window ... |