Literature DB >> 19226669

Can complex cellular processes be governed by simple linear rules?

Kumar Selvarajoo1, Masaru Tomita, Masa Tsuchiya.   

Abstract

Complex living systems have shown remarkably well-orchestrated, self-organized, robust, and stable behavior under a wide range of perturbations. However, despite the recent generation of high-throughput experimental datasets, basic cellular processes such as division, differentiation, and apoptosis still remain elusive. One of the key reasons is the lack of understanding of the governing principles of complex living systems. Here, we have reviewed the success of perturbation-response approaches, where without the requirement of detailed in vivo physiological parameters, the analysis of temporal concentration or activation response unravels biological network features such as causal relationships of reactant species, regulatory motifs, etc. Our review shows that simple linear rules govern the response behavior of biological networks in an ensemble of cells. It is daunting to know why such simplicity could hold in a complex heterogeneous environment. Provided physical reasons can be explained for these phenomena, major advancement in the understanding of basic cellular processes could be achieved.

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Year:  2009        PMID: 19226669     DOI: 10.1142/s0219720009003947

Source DB:  PubMed          Journal:  J Bioinform Comput Biol        ISSN: 0219-7200            Impact factor:   1.122


  11 in total

1.  Analysis of the molecular networks in androgen dependent and independent prostate cancer revealed fragile and robust subsystems.

Authors:  Ryan Tasseff; Satyaprakash Nayak; Saniya Salim; Poorvi Kaushik; Noreen Rizvi; Jeffrey D Varner
Journal:  PLoS One       Date:  2010-01-28       Impact factor: 3.240

2.  Propagation of kinetic uncertainties through a canonical topology of the TLR4 signaling network in different regions of biochemical reaction space.

Authors:  Jayson Gutiérrez; Georges St Laurent; Silvio Urcuqui-Inchima
Journal:  Theor Biol Med Model       Date:  2010-03-15       Impact factor: 2.432

3.  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

4.  Macroscopic law of conservation revealed in the population dynamics of Toll-like receptor signaling.

Authors:  Kumar Selvarajoo
Journal:  Cell Commun Signal       Date:  2011-04-20       Impact factor: 5.712

5.  Enhancing apoptosis in TRAIL-resistant cancer cells using fundamental response rules.

Authors:  Vincent Piras; Kentaro Hayashi; Masaru Tomita; Kumar Selvarajoo
Journal:  Sci Rep       Date:  2011-11-07       Impact factor: 4.379

6.  Systems Biology Strategy Reveals PKCδ is Key for Sensitizing TRAIL-Resistant Human Fibrosarcoma.

Authors:  Kentaro Hayashi; Sho Tabata; Vincent Piras; Masaru Tomita; Kumar Selvarajoo
Journal:  Front Immunol       Date:  2015-01-05       Impact factor: 7.561

7.  Parameter-less approaches for interpreting dynamic cellular response.

Authors:  Kumar Selvarajoo
Journal:  J Biol Eng       Date:  2014-08-19       Impact factor: 4.355

Review 8.  Systems biology approaches integrated with artificial intelligence for optimized metabolic engineering.

Authors:  Mohamed Helmy; Derek Smith; Kumar Selvarajoo
Journal:  Metab Eng Commun       Date:  2020-10-09

9.  Predicting novel features of toll-like receptor 3 signaling in macrophages.

Authors:  Mohamed Helmy; Jin Gohda; Jun-Ichiro Inoue; Masaru Tomita; Masa Tsuchiya; Kumar Selvarajoo
Journal:  PLoS One       Date:  2009-03-02       Impact factor: 3.240

10.  A systems biology approach to suppress TNF-induced proinflammatory gene expressions.

Authors:  Kentaro Hayashi; Vincent Piras; Sho Tabata; Masaru Tomita; Kumar Selvarajoo
Journal:  Cell Commun Signal       Date:  2013-11-07       Impact factor: 5.712

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