Utility and Limitations of Using Gene Expression Data to Identify Functional Associations
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DOI: 10.1371/journal.pcbi.1005244
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References listed on IDEAS
- Zhang Bin & Horvath Steve, 2005. "A General Framework for Weighted Gene Co-Expression Network Analysis," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 4(1), pages 1-45, August.
- Schäfer Juliane & Strimmer Korbinian, 2005. "A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 4(1), pages 1-32, November.
- Robert Tibshirani & Guenther Walther & Trevor Hastie, 2001. "Estimating the number of clusters in a data set via the gap statistic," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 411-423.
- Smyth Gordon K, 2004. "Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 3(1), pages 1-28, February.
- Zing Tsung-Yeh Tsai & Shin-Han Shiu & Huai-Kuang Tsai, 2015. "Contribution of Sequence Motif, Chromatin State, and DNA Structure Features to Predictive Models of Transcription Factor Binding in Yeast," PLOS Computational Biology, Public Library of Science, vol. 11(8), pages 1-22, August.
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