Network-based Observability and Controllability Analysis of Dynamical Systems: the NOCAD toolbox.

Dániel Leitold, Ágnes Vathy-Fogarassy, János Abonyi

Abstract read

In one paragraph

Article in F1000Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Dániel LeitoldDepartment of Computer Science and Systems Technology, University of Pannonia, Egyetem u. 10, Veszprém, 8200, Hungary.ORCID 0000-0003-2644-8164

Ágnes Vathy-FogarassyDepartment of Computer Science and Systems Technology, University of Pannonia, Egyetem u. 10, Veszprém, 8200, Hungary.ORCID 0000-0002-5524-1675

János AbonyiMTA-PE Lendulet Complex Systems Monitoring Research Group, University of Pannonia, Egyetem u. 10, POB. 158, Veszprém, 8200, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The network science-based determination of driver nodes and sensor placement has become increasingly popular in the field of dynamical systems over the last decade. In this paper, the applicability of the methodology in the field of life sciences is introduced through the analysis of the neural network of Caenorhabditis elegans. Simultaneously, an Octave and MATLAB-compatible NOCAD toolbox is proposed that provides a set of methods to automatically generate the relevant structural controllability and observability associated measures for linear or linearised systems and compare the different sensor placement methods.

Indexed as

AlgorithmsCaenorhabditis elegansAnimalsNeural Networks, ComputerComplex networksControllability and observability analysisDynamical systemsMATLAB toolboxRobustness

Identifiers

PMID31608146

DOI10.12688/f1000research.19029.2

PMCPMC6777013

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LicenceCC BY

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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.