Co-clustering of biological networks and gene expression data
By Daniel Hanisch, Alexander Zien, Ralf Zimmer, Thomas Lengauer. Intelligent Systems in Molecular Biology, 2002
369 citations recorded by the source corpus.
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/d1b2996bdbbe2a643f6ba187938d6b921464a17f
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Citations in the corpus
- Genome-scale models of bacterial metabolism: reconstruction and applications (2008, methodology): “In the vein of pathway-or module-based methods interpreting changes of gene expressions at the level of pathways or biological processes (Hanisch et al ., 2002; Draghici et al ., 2003; Yang et al ., 2004), methods relying on a graph representation of metabolism (Patil & Nielsen, 2005) or on a…”
- Identification of functional modules using network topology and high-throughput data (2007, methodology): “[17], which proposes a distance measure based on topology and expression.”
- Metabolomics in systems biology. (2003, background): “Thus, we are still searching for the metabolic network that comprises the real cell state, the instantaneous active pathway, in a complex theoretical network under certain conditions (32, 61).”
- Efficient community detection in large networks using content and links (2012, methodology): “Biologists have studied methods [13, 26] to find functional modules using network topology and gene expression data.”
- Local Modeling of Attributed Graphs: Algorithms and Applications (2016, methodology): “The representative methods [3, 51, 60, 82, 137, 154] aim to partition the given graph into structurally dense and attribute-wise homogeneous clusters, detect deviations from frequent subgraphs [110], or search for community outliers in attributed graphs [51].”
- Multiconstrained gene clustering based on generalized projections (2010, methodology): “Because the Pearson’s correlation coefficient is suitable for time-series gene expression data [26], we adopt it for calculating the similarity between two genes’ log-ratio transformed profiles [8], i.”
- Clustering attributed graphs: Models, measures and methods (2015, methodology): “Hanisch et al. (2002) experiment with a similar approach on biological networks and gene expression data.”