Literature DB >> 21554129

Determining a singleton attractor of a boolean network with nested canalyzing functions.

Tatsuya Akutsu1, Avraham A Melkman, Takeyuki Tamura, Masaki Yamamoto.   

Abstract

In this article, we study the problem of finding a singleton attractor for several biologically important subclasses of Boolean networks (BNs). The problem of finding a singleton attractor in a BN is known to be NP-hard in general. For BNs consisting of n nested canalyzing functions, we present an O(1.799(n)) time algorithm. The core part of this development is an O(min(2(k/2) · 2(m/2), 2(k)) · poly(k, m)) time algorithm for the satisfiability problem for m nested canalyzing functions over k variables. For BNs consisting of chain functions, a subclass of nested canalyzing functions, we present an O(1.619(n)) time algorithm and show that the problem remains NP-hard, even though the satisfiability problem for m chain functions over k variables is solvable in polynomial time. Finally, we present an o(2(n)) time algorithm for bounded degree BNs consisting of canalyzing functions.

Mesh:

Year:  2011        PMID: 21554129     DOI: 10.1089/cmb.2010.0281

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  7 in total

Review 1.  Qualitative Modeling, Analysis and Control of Synthetic Regulatory Circuits.

Authors:  Madalena Chaves; Hidde de Jong
Journal:  Methods Mol Biol       Date:  2021

2.  Learning delayed influences of biological systems.

Authors:  Tony Ribeiro; Morgan Magnin; Katsumi Inoue; Chiaki Sakama
Journal:  Front Bioeng Biotechnol       Date:  2015-01-16

3.  On control of singleton attractors in multiple Boolean networks: integer programming-based method.

Authors:  Yushan Qiu; Takeyuki Tamura; Wai-Ki Ching; Tatsuya Akutsu
Journal:  BMC Syst Biol       Date:  2014-01-24

4.  An Efficient Steady-State Analysis Method for Large Boolean Networks with High Maximum Node Connectivity.

Authors:  Changki Hong; Jeewon Hwang; Kwang-Hyun Cho; Insik Shin
Journal:  PLoS One       Date:  2015-12-30       Impact factor: 3.240

5.  An Algorithm for Finding the Singleton Attractors and Pre-Images in Strong-Inhibition Boolean Networks.

Authors:  Zhiwei He; Meng Zhan; Shuai Liu; Zebo Fang; Chenggui Yao
Journal:  PLoS One       Date:  2016-11-18       Impact factor: 3.240

6.  Robustness and backbone motif of a cancer network regulated by miR-17-92 cluster during the G1/S transition.

Authors:  Lijian Yang; Yan Meng; Chun Bao; Wangheng Liu; Chengzhang Ma; Anbang Li; Zhan Xuan; Ge Shan; Ya Jia
Journal:  PLoS One       Date:  2013-03-01       Impact factor: 3.240

7.  Automatic Screening for Perturbations in Boolean Networks.

Authors:  Julian D Schwab; Hans A Kestler
Journal:  Front Physiol       Date:  2018-04-24       Impact factor: 4.566

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.