Evidence map›Paper›PMID 27187990›Full record

ArticleIET systems biology2016

Minimum steering node set of complex networks and its applications to biomolecular networks.

Lin Wu, Min Li, Jianxin Wang, Fang-Xiang Wu

Open access · greenAbstract read
In one paragraph

Article in IET systems biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.1field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

2 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. 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 at 3 institutions in 2 countries.

Lin WuDivision of Biomedical Engineering, University of Saskatchewan, Saskatoon, Canada, SK S7N 5A9.
Min LiSchool of Information Science and Engineering, Central South University, Changsha, Hunan 410083, People's Republic of China.
Jianxin WangSchool of Information Science and Engineering, Central South University, Changsha, Hunan 410083, People's Republic of China.
Fang-Xiang WuSchool of Mathematical Sciences, Nankai University, Tianjin 300071, People's Republic of China. faw341@mail.usask.ca.
Central South University · CNNankai University · CNUniversity of Saskatchewan · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many systems of interests in practices can be represented as complex networks. For biological systems, biomolecules do not perform their functions alone but interact with each other to form so-called biomolecular networks. A system is said to be controllable if it can be steered from any initial state to any other final state in finite time. The network controllability has become essential to study the dynamics of the networks and understand the importance of individual nodes in the networks. Some interesting biological phenomena have been discovered in terms of the structural controllability of biomolecular networks. Most of current studies investigate the structural controllability of networks in notion of the minimum driver node sets (MDSs). In this study, the authors analyse the network structural controllability in notion of the minimum steering node sets (MSSs). They first develop a graph-theoretic algorithm to identify the MSS for a given network and then apply it to several biomolecular networks. Application results show that biomolecules identified in the MSSs play essential roles in corresponding biological processes. Furthermore, the application results indicate that the MSSs can reflect the network dynamics and node importance in controlling the networks better than the MDSs.

Indexed as

AlgorithmsModels, BiologicalAnimalsComputer SimulationHumansProteomeSignal TransductionProteome

Identifiers

PMID27187990
PMCPMC8687185
OpenAlexW2318071399

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.