Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genomewide data.

By Amos Tanay, Roded Sharan, M. Kupiec, Ron Shamir. Proceedings of the National Academy of Sciences of the United States of America, 2004

429 citations recorded by the source corpus.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/311d4031859cbbbe1985369e3883ff6261a03db7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Jian Peng
2. Bonnie Berger
3. Mona Singh
4. Igor Ulitsky
5. Roded Sharan
6. Ron Shamir
7. Leroy Hood
8. Richard Bonneau

Citations in the corpus

• In silico prediction of protein-protein interactions in human macrophages (2001, background): “…functional maps to help the user to build functional hypothesis [28] and in the analysis of a diverse collection of genome-wide data sets (gene expression, protein interactions, growth phenotype data, and transcription factor binding) to decipher the yeast system modular organisation [42].”
• Approximating the cut-norm via Grothendieck's inequality (2004, background): “While trying to identify groups of genes with statistically significant correlated behaviour across diverse experiments, it is desirable to solve a certain biclustering problem, see [27], [26].”
• Computational solutions for omics data (2013, methodology): “To accomplish these tasks, numerous statistical methods, such as gene set enrichment analysis (GSEA) 71 , GenePattern 72 , joint clustering 73,74 and DEseq 75 , have been devised and widely applied to analyse differentially expressed genes and gene sets 56,57 .”
• Biclustering in data mining (2008, background): “Agreatvarietyofbiclusteringmethodsthathavebeenusedinmicroarray dataanalysisaredescribedin[19,27,29,33,37,39,43,45,46,48].”
• The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo (2006, background): “Biclustering was developed to address better the full complexity of finding co-regulated genes under multifactor control by grouping genes on the basis of coherence under subsets of observed conditions [10,16-22].”
• Introduction to systems biology. (2007, background): “Most noticeably are small world organization [57, 58], modularity [59, 60], motifs [61–63], fl ux balance analysis, extreme pathway and elementary mode analysis [6, 64–67].”
• Network-based prediction of protein function (2007, methodology): “A natural question is the relation between transcription pattern similarity of a pair of genes and the existence of a protein interaction between their products.”
• Robustness of Cellular Functions (2004, neutral): “tradeoffs, (Segal et al., 2003; Ihmels et al., 2004), and integrated networks (Tanay et al., 2004).”