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Literature DB >> 18793131

Network reconstruction based on steady-state data.

Abstract

This paper discusses a theoretical method for the "reverse engineering" of networks based solely on steady-state (and quasi-steady-state) data.

Mesh：

Year: 2008 PMID： 18793131 DOI： 10.1042/BSE0450161

Source DB: PubMed Journal: Essays Biochem ISSN： 0071-1365 Impact factor: 8.000

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Cited

13 in total

1. Gene regulatory network modeling using literature curated and high throughput data.

Authors: Vishwesh V Kulkarni; Reza Arastoo; Anupama Bhat; Kalyansundaram Subramanian; Mayuresh V Kothare; Marc C Riedel
Journal: Syst Synth Biol Date: 2012-12-07

2. Reverse engineering validation using a benchmark synthetic gene circuit in human cells.

Authors: Taek Kang; Jacob T White; Zhen Xie; Yaakov Benenson; Eduardo Sontag; Leonidas Bleris
Journal: ACS Synth Biol Date: 2013-03-28 Impact factor: 5.110

3. Feedback analysis identifies a combination target for overcoming adaptive resistance to targeted cancer therapy.

Authors: Sang-Min Park; Chae Young Hwang; Jihye Choi; Chang Young Joung; Kwang-Hyun Cho
Journal: Oncogene Date: 2020-03-10 Impact factor: 9.867

4. Reconstruction of Gene Regulatory Networks based on Repairing Sparse Low-rank Matrices.

Authors: Young Hwan Chang; Roel Dobbe; Palak Bhushan; Joe W Gray; Claire J Tomlin
Journal: IEEE/ACM Trans Comput Biol Bioinform Date: 2015-08-07 Impact factor: 3.710

5. Silence on the relevant literature and errors in implementation.

Authors: Philippe Bastiaens; Marc R Birtwistle; Nils Blüthgen; Frank J Bruggeman; Kwang-Hyun Cho; Carlo Cosentino; Alberto de la Fuente; Jan B Hoek; Anatoly Kiyatkin; Steffen Klamt; Walter Kolch; Stefan Legewie; Pedro Mendes; Takashi Naka; Tapesh Santra; Eduardo Sontag; Hans V Westerhoff; Boris N Kholodenko
Journal: Nat Biotechnol Date: 2015-04 Impact factor: 54.908

Network reconstruction based on steady-state data.

1. Gene regulatory network modeling using literature curated and high throughput data.

2. Reverse engineering validation using a benchmark synthetic gene circuit in human cells.

3. Feedback analysis identifies a combination target for overcoming adaptive resistance to targeted cancer therapy.

4. Reconstruction of Gene Regulatory Networks based on Repairing Sparse Low-rank Matrices.

5. Silence on the relevant literature and errors in implementation.

6. A Sparse Reconstruction Approach for Identifying Gene Regulatory Networks Using Steady-State Experiment Data.

7. Uncovering hidden nodes in complex networks in the presence of noise.

8. Data-based reconstruction of complex geospatial networks, nodal positioning and detection of hidden nodes.

9. A stochastic model for microtubule motors describes the in vivo cytoplasmic transport of human adenovirus.

10. Exact reconstruction of gene regulatory networks using compressive sensing.