Structure and evolution of transcriptional regulatory networks.

By M. Babu, Nicholas M. Luscombe, L. Aravind, Mark Gerstein, Sarah A. Teichmann. Current Opinion in Structural Biology, 2004

853 citations recorded by the source corpus.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/176c6e22f933647406f020841b54a2e3f2da7e54

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Citations in the corpus

Polycomb group proteins: navigators of lineage pathways led astray in cancer (2009, neutral): “So which transcription factors control the association of PcG proteins with their target genes? It has been estimated that the human genome encodes approximately 2,600 transcription factor”
High-resolution detection of DNA binding sites of the global transcriptional regulator GlxR in Corynebacterium glutamicum. (2013, background): “These networks are composed of transcriptional regulatory proteins, their target genes and the regulatory interactions exerted (Babu et al., 2004).”
Analyzing and modeling real-world phenomena with complex networks: a survey of applications (2007, methodology): “The evolution of transcriptional regulatory networks occu rs via three processes: (i) duplication of the transcription factor, which results in both copies re gulating the same gene, (ii) duplication of the target gene with its regulatory region, where the target gene will be regulated by the same t”
Mapping genome-wide transcription-factor binding sites using DAP-seq (2017, background): “%) to the expression of between 1000–2500 DNA-binding transcription factors 3 .”
Analysis of Biological Networks (2008, background): “While random attacks will most likely affect low degree vertices, a selective attack on high degree vertices has far more dramatic consequence on global network indices [1,2,29].”
The Importance of Bottlenecks in Protein Networks: Correlation with Gene Essentiality and Expression Dynamics (2007, background): “Likewise, while many studies addressed relations between the interaction network and protein function, they only make use of local network features, such as distance [39–42].”
Function of alternative splicing. (2005, neutral): “However, there are less than 50 proteins known that regulate alternative splicing and less than 300 proteins known that bind RNA (Chen and Manley, 2009; Graveley, 2009), which contrasts with the more than 2500 identified transcription factors (Babu et al., 2004).”
Regulation of transcription from the fusion promoters generated by transposition of Tn4652 into the upstream region of pheBA operon in Pseudomonas putida (2005, background): “It was shown lately that transcriptional regulators controlling the physiological state of bacteria are in hierarchical connections (MartinezAntonio and Collado-Vides, 2003; Babu et al., 2004).”
An interaction-motif-based scoring function for protein-ligand docking (2010, background): “While a number of algorithms for discovering network motifs have been reported [28-32], they could not be easily adopted here because the protein-ligand interaction networks constructed in this study are a bipartite network, which is different from the conventional gene-gene or protein-protein…”
Mechanisms of alternative splicing regulation: insights from molecular and genomics approaches (2009, background): “Importantly, >2,500 transcription factors have been identified in human”
The many faces of the helix-turn-helix domain: transcription regulation and beyond. (2005, methodology): “Alternatively, the alignments were used to generate hidden Markov models, which were similarly used to search the proteomes with the HMMER program [42].”
Network motifs: theory and experimental approaches (2007, background): “A view of network-motif behaviour within the global dynamics of gene networks can be gleaned by means of DNA microarray”
Network Inference and Biological Dynamics (2011, background): “For example, in a gene regulatory network [Babu et al. (2004); Davidson (2001)], nodes represent genes and edges transcriptional regulation, while in a protein signaling network [Yarden and nardo (2007); Li and Chen (2010); Nam, Yoon and Kim (2007)] are intimately related, being based on linear…”
Graph theory and networks in Biology. (2006, background): “A loose hierarchical structure for bio-molecular networks was proposed in [2, 147].”