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Omics derived networks in bacteria

(2013) CURRENT BIOINFORMATICS. 8(4). p.489-495
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Bioinformatics: from nucleotids to networks (N2N)
Abstract
Understanding the cellular behavior from a systems perspective requires the identification of functional and physical interactions among diverse molecular entities in a cell (i.e. DNA/RNA, proteins and metabolites). Powerful and scalable technologies enabled the generation of genome-wide datasets that describe cellular systems by capturing the interactions of their building blocks under different environmental stimuli. The most straightforward way to represent such datasets is by means of molecular networks of which nodes correspond to molecular entities and edges to the interactions amongst those entities. In this review we give an overview of the different functional and physical interaction networks in bacteria that have been or potentially can be built by the integration of diverse omics datasets.
Keywords
ESCHERICHIA COLI K-12, SCALE METABOLIC RECONSTRUCTION, Bacteria, dataintegration, molecular networks, network inference, omics data, REGULATORY NETWORKS, TRANSCRIPTIONAL REGULATION, INTERACTION MAP, HIGH-THROUGHPUT, COMPLEX NETWORKS, TOPOLOGICAL INDEXES, DRUG METABOLISM, PROTEIN-PROTEIN INTERACTION

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Citation

Please use this url to cite or link to this publication:

Chicago
Sánchez-Rodríguez, Aminael, Lore Cloots, and Kathleen Marchal. 2013. “Omics Derived Networks in Bacteria.” Current Bioinformatics 8 (4): 489–495.
APA
Sánchez-Rodríguez, A., Cloots, L., & Marchal, K. (2013). Omics derived networks in bacteria. CURRENT BIOINFORMATICS, 8(4), 489–495.
Vancouver
1.
Sánchez-Rodríguez A, Cloots L, Marchal K. Omics derived networks in bacteria. CURRENT BIOINFORMATICS. 2013;8(4):489–95.
MLA
Sánchez-Rodríguez, Aminael, Lore Cloots, and Kathleen Marchal. “Omics Derived Networks in Bacteria.” CURRENT BIOINFORMATICS 8.4 (2013): 489–495. Print.
@article{4180228,
  abstract     = {Understanding the cellular behavior from a systems perspective requires the identification of functional and physical interactions among diverse molecular entities in a cell (i.e. DNA/RNA, proteins and metabolites). Powerful and scalable technologies enabled the generation of genome-wide datasets that describe cellular systems by capturing the interactions of their building blocks under different environmental stimuli. The most straightforward way to represent such datasets is by means of molecular networks of which nodes correspond to molecular entities and edges to the interactions amongst those entities. In this review we give an overview of the different functional and physical interaction networks in bacteria that have been or potentially can be built by the integration of diverse omics datasets.},
  author       = {S{\'a}nchez-Rodr{\'i}guez, Aminael and Cloots, Lore and Marchal, Kathleen},
  issn         = {1574-8936},
  journal      = {CURRENT BIOINFORMATICS},
  keyword      = {ESCHERICHIA COLI K-12,SCALE METABOLIC RECONSTRUCTION,Bacteria,dataintegration,molecular networks,network inference,omics data,REGULATORY NETWORKS,TRANSCRIPTIONAL REGULATION,INTERACTION MAP,HIGH-THROUGHPUT,COMPLEX NETWORKS,TOPOLOGICAL INDEXES,DRUG METABOLISM,PROTEIN-PROTEIN INTERACTION},
  language     = {eng},
  number       = {4},
  pages        = {489--495},
  title        = {Omics derived networks in bacteria},
  volume       = {8},
  year         = {2013},
}

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