Shuffling Yeast Gene Expression Data

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dc.creatorBilke, Sven
dc.date2000-06-20
dc.date.accessioned2026-07-07T05:44:13Z
dc.date.available2026-07-07T05:44:13Z
dc.descriptionA new method to sort gene expression patterns into functional groups is presented. The method is based on a sorting algorithm using a non-local similarity score, which takes all other patterns in the dataset into account. The method is therefore very robust with respect to noise. Using the expression data for yeast, we extract information about functional groups. Without prior knowledge of parameters the cell cycle regulated genes in yeast can be identified. Furthermore a second, independent cell clock is identified. The capability of the algorithm to extract information about signal flow in the regulatory network underlying the expression patterns is demonstrated.
dc.description8 pages, 2 figures. Submitted to Proceedings of the National Academy of Science USA
dc.identifierhttps://arxiv.org/abs/physics/0006050
dc.identifierhttp://arxiv.org/abs/physics/0006050
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/83554
dc.subjectBiological Physics
dc.subjectData Analysis, Statistics and Probability
dc.subjectMedical Physics
dc.subjectQuantitative Methods
dc.titleShuffling Yeast Gene Expression Data
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