Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements.

By Atul J. Butte, I. Kohane. 1999

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Citations in the corpus

Mutual Information Neural Estimation (2018, background): “…tasks, including biomedical sciences (Maes et al., 1997), blind source separation (BSS, e.g., independent component analysis, Hyv¨arinen et al., 2004), information bottleneck (IB, Tishby et al., 2000), feature selection (Kwak & Choi, 2002; Peng et al., 2005), and causality (Butte & Kohane, 2000).”
Data Based Identification and Prediction of Nonlinear and Complex Dynamical Systems (2016, methodology): “In RELNET, a threshold τ is used to distinguish actual links from null connections.”
Reverse engineering of regulatory networks in human B cells (2005, background): “, which combine data from a number of independent experimental clues; and statistical method”
Next-Generation Machine Learning for Biological Networks. (2018, unknown): “The area has benefited from machine learning largely in the identification of network architectures (Butte and Kohane, 2000; Cahan et al., 2014; Faith et al., 2007; Friedman, 2004; Margolin et al., 2006).”
A new approach to decoding life: systems biology. (2001, methodology): “Several clustering methods have been proposed: Most are excellent and have associated software packages that are publicly available (4, 23, 25, 36, 39, 57, 62, 118).”
Equitability, mutual information, and the maximal information coefficient (2013, methodology): “medical imaging [38], and signal processing [39]. We also note that mutual information has been used by multiple groups to construct networks analogous to those constructed by Reshef et al. using MIC [3, 40, 41, 42, 43]. We emphasize, however, that all the diculties associated with estimating mutual”
From patterns to pathways: gene expression data analysis comes of age (2002, background): “Even simple pairwise comparisons can indicate novel interactions 78 .”
The mutual information: Detecting and evaluating dependencies between variables (2002, methodology): “This approach is not entirely new: An early attempt to use information-theoretic concepts in this context was given in (Michaels et al. , 1998), a more recent analysis was applied by Butte and Kohane (2000).”
Genetic network inference: from co-expression clustering to reverse engineering (2000, background): “Section”
Inferring cellular networks – a review (2007, background): “This problem can be addressed by using networks built from more flexible similarity measures like pair-wise mutual information [13], or non-linear kernel-functions [14].”
Molecular ecological network analyses (2012, methodology): “Similar to relevant gene co-expression network analysis [20,61,85,86], the nodes are connected if they have significant pairwise similarities (i.”
Inferring gene regulatory networks from gene expression data by path consistency algorithm based on conditional mutual information (2012, background): “Second, MI is more general than PCC to model the relations between genes, while PCC is more easily distorted when points are not uniformly distributed across the axes (Butte and Kohane, 2000).”