Literature DB >> 14641103

Reconstructing gene networks: what are the limits?

J Stark1, D Brewer, M Barenco, D Tomescu, R Callard, M Hubank.   

Abstract

To fully realize the benefits of high-throughput post-genomic technologies it is necessary to reconstruct and analyse the complicated network of interactions through which most genes operate. We briefly summarize the mathematical frameworks that can be used to model such networks, and the types of algorithms available for their reconstruction. We then focus on dynamic models, typically described using differential equations, and explain the two main reconstruction approaches in current use. We discuss the data requirements of these algorithms and ask how well they correspond to current microarray data.

Mesh:

Year:  2003        PMID: 14641103     DOI: 10.1042/bst0311519

Source DB:  PubMed          Journal:  Biochem Soc Trans        ISSN: 0300-5127            Impact factor:   5.407


  6 in total

1.  Reconstruction of extended Petri nets from time series data and its application to signal transduction and to gene regulatory networks.

Authors:  Markus Durzinsky; Annegret Wagler; Wolfgang Marwan
Journal:  BMC Syst Biol       Date:  2011-07-15

2.  Reconstructing gene-regulatory networks from time series, knock-out data, and prior knowledge.

Authors:  Florian Geier; Jens Timmer; Christian Fleck
Journal:  BMC Syst Biol       Date:  2007-02-02

3.  Using large-scale perturbations in gene network reconstruction.

Authors:  Thomas MacCarthy; Andrew Pomiankowski; Robert Seymour
Journal:  BMC Bioinformatics       Date:  2005-01-19       Impact factor: 3.169

4.  Reconstruction of dynamic regulatory networks reveals signaling-induced topology changes associated with germ layer specification.

Authors:  Emily Y Su; Abby Spangler; Qin Bian; Jessica Y Kasamoto; Patrick Cahan
Journal:  Stem Cell Reports       Date:  2022-01-27       Impact factor: 7.294

5.  Ranked prediction of p53 targets using hidden variable dynamic modeling.

Authors:  Martino Barenco; Daniela Tomescu; Daniel Brewer; Robin Callard; Jaroslav Stark; Michael Hubank
Journal:  Genome Biol       Date:  2006-03-31       Impact factor: 13.583

Review 6.  Single-cell transcriptome sequencing: recent advances and remaining challenges.

Authors:  Serena Liu; Cole Trapnell
Journal:  F1000Res       Date:  2016-02-17
  6 in total

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