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Gene expression

Predictions across space and time

Nature Reviews Genetics volume 14, pages 78–79 (2013)Cite this article

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Increasingly large amounts of data are becoming available that can be used in predicting gene expression patterns. For example, data from chromatin immunoprecipitation followed by microarray (ChIP–chip) or by high-throughput sequencing (ChIP–seq) make possible the identification of regulatory elements, such as enhancers, that are bound by specific transcription factors. The same technology can determine whether a gene is surrounded by 'active' or 'inactive' chromatin marks. A key challenge in predicting gene expression lies in integrating these different types of data. In addition, important information is missing, such as a complete view of all of the enhancers that are active in a particular stage of development.

the model takes a vital first step towards [predicting] spatiotemporal expression patterns in a multicellular context

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ORIGINAL RESEARCH PAPER

  1. Wilczynski, B. et al. Predicting spatial and temporal gene expression using an integrative model of transcription factor occupancy and chromatin state. PLoS Comput. Biol. 8, e1002798 (2012)

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  1. Louisa Flintoft
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Flintoft, L. Predictions across space and time. Nat Rev Genet 14, 78–79 (2013). https://doi.org/10.1038/nrg3411

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