Reverse engineering gene networks: Integrating genetic perturbations with dynamical modeling

By Jesper N. Tegnér, M. K. S. Yeung, Jeff Hasty, James J. Collins. Proceedings of the National Academy of Sciences of the United States of America, 2003

473 citations recorded by the source corpus.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/48cffbd099578677013526b7a3d6e9ff4ff59aba

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Citations in the corpus

Inverse statistical problems: from the inverse Ising problem to data science (2017, methodology): “A second line of approach that can provide information on regulatory connections is perturbations [218].”
Gene regulatory network inference: Data integration in dynamic models - A review (2009, methodology): “The underlying concept of iterated and systematic perturbations was also used by Tegner et al. (2003).”
TIGRESS: Trustful Inference of Gene REgulation using Stability Selection (2012, methodology): “Moreover, running TIGRESS online is possible on GenePattern: http://www.broadinstitute.org/ cancer/software/genepattern/.”
Control Principles of Complex Networks (2015, background): “It has been well established for the reconstruction of gene regulatory networks (Gardner et al., 2003; Tegner et al., 2003; Yu, 2010; Yu and Parlitz, 2010).”
Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, methodology): “…methodologies (Liang et al., 1998a; Akutsu et al., 1999; Ideker et al., 2000; Kholodenko et al., 2002; Yeung et al., 2002; Segal et al., 2003; Tegnér et al., 2003; Friedman, 2004; Tegnér & Bjorkegren, 2007; Cosgrove et al., 2008; Kim et al., 2008; Ahmed & Xing, 2009; Stokic et al., 2009;…”
Current approaches to gene regulatory network modelling (2007, background): “[ 97].”
ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context (2004, background): “However, studies based on targeted perturbations to model organisms have demonstrated the promise of using conceptual "gene-gene" networks to elucidate functional mechanisms underlying cellular processes [31] as well as to identify molecular targets of pharmacological compounds [32].”
Sparse multitask regression for identifying common mechanism of response to therapeutic targets (2010, unknown): “Contact: b_parvin@lbl.gov”
Large-Scale Mapping and Validation of Escherichia coli Transcriptional Regulation from a Compendium of Expression Profiles (2007, background): “Pioneering efforts to identify regulatory interactions on a genome scale have used machine-learning algorithms to identify cis-regulatory motifs or transcription factor target genes using a large set of expression arrays [2–18], genomewide location analysis chromatin immunoprecipitation (ChIP-Chip) ”
The efficiency of multi-target drugs: the network approach might help drug design. (2004, methodology): “The extension of current experimental [25-28] and modeling [2022,29-33] approaches to perturb networks and mimic the effect of multi-target drugs would test the generality of our assumptions.”
How to infer gene networks from expression profiles (2007, methodology): “Other algorithms based on ODEs have been proposed in the literature (D’haeseleer et al , 1999; Tegner et al , 2003; Bonneau et al , 2006; van Someren et al , 2006).”
Inferring cellular networks – a review (2007, methodology): “For reconstruction of regulatory networks, a number of methods have been proposed in different frameworks: for Bayesian networks [120,121], physical network models [122], Boolean networks [102], and dynamical modeling [123].”
Inference of gene regulatory networks and compound mode of action from time course gene expression profiles (2006, methodology): “…used to describe genetic networks (de Jong, 2002; Savageau, 2001; Levchenko and Iglesias, 2002), including Boolean logic (Shmulevich et al., 2002; Liang et al., 1998), Bayesian networks (Hartemink et al., 2002), graph theory (Wagner, 2001) and ordinary differential equations (Tegner et al., 2003).”
The Emerging Paradigm of Network Medicine in the Study of Human Disease (2012, background): “Indeed, such processes have been validated in small sets of discrete gene networks active in organisms, such as bacteria, 58 yeast, 59 and Drosophila , 60 as well as for mapping networks of small noncoding RNA in bacteria.”