Evidence map›Paper›PMID 24565276›Full record

ArticleBMC systems biology2014

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

Yushan Qiu, Takeyuki Tamura, Wai-Ki Ching, Tatsuya Akutsu

Abstract read
In one paragraph

Article in BMC systems biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Exploring Observability of Attractor Cycles in Boolean Networks for Biomarker Detection.IEEE access : practical innovations, open solutions · 2019
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Attractor-Based Obstructions to Growth in Homogeneous Cyclic Boolean Automata.Journal of computer science and systems biology · 2015
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yushan Qiu
Takeyuki Tamura
Wai-Ki Ching
Tatsuya Akutsu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBoolean network (BN) is a mathematical model for genetic network and control of genetic networks has become an important issue owing to their potential application in the field of drug discovery and treatment of intractable diseases. Early researches have focused primarily on the analysis of attractor control for a randomly generated BN. However, one may also consider how anti-cancer drugs act in both normal and cancer cells. Thus, the development of controls for multiple BNs is an important and interesting challenge.

resultsIn this article, we formulate three novel problems about attractor control for two BNs (i.e., normal cell and cancer cell). The first is about finding a control that can significantly damage cancer cells but has a limited damage to normal cells. The second is about finding a control for normal cells with a guaranteed damaging effect on cancer cells. Finally, we formulate a definition for finding a control for cancer cells with limited damaging effect on normal cells. We propose integer programming-based methods for solving these problems in a unified manner, and we conduct computational experiments to illustrate the efficiency and the effectiveness of our method for our multiple-BN control problems.

conclusionsWe present three novel control problems for multiple BNs that are realistic control models for gene regulation networks and adopt an integer programming approach to address these problems. Experimental results indicate that our proposed method is useful and effective for moderate size BNs.

Indexed as

Gene Regulatory NetworksModels, GeneticAlgorithmsComputational BiologyNeoplasms

Identifiers

PMID24565276
PMCPMC4080371

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.