Approximate entropy of network parameters

West, James D.; Lacasa, Lucas; Severini, Simone; Teschendorff, Andrew E.

doi:10.1103/physreve.85.046111

Cited by 15 publications

(7 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…See [15] for more methods and metrics for carrying out this kind of analysis. See also [32] for a revision of different approximations to entropy for network parameters.…”

Section: Introductionmentioning

confidence: 99%

Visibility graphs of fractional Wu–Baleanu time series

Conejero

Lizama

Mira‐Iglesias

et al. 2019

Journal of Difference Equations and Applications

View full text Add to dashboard Cite

We study time series generated by the parametric family of fractional discrete maps introduced by Wu and Baleanu in [34], presenting an alternative way of introducing these maps. For the values of the parameters that yield chaotic time series, we have studied the Shannon entropy of the degree distribution of the natural and horizontal visibility graphs associated to these series. In these cases, the degree distribution can be fitted with a power law. We have also compared the Shannon entropy and the exponent of the power law fitting for the different values of the fractionary exponent and the scaling factor of the model. Our results illustrate a connection between the fractionary exponent and the scaling factor of the maps, with the respect to the onset of the chaos.

show abstract

“…See [15] for more methods and metrics for carrying out this kind of analysis. See also [32] for a revision of different approximations to entropy for network parameters.…”

Section: Introductionmentioning

confidence: 99%

Visibility graphs of fractional Wu–Baleanu time series

Conejero

Lizama

Mira‐Iglesias

et al. 2019

Journal of Difference Equations and Applications

View full text Add to dashboard Cite

show abstract

“…Recently, Teschendorff and Severini, using methods of mathematical inference and the analysis of gene expression patterns, expressed a method to validate the cellular network entropy [ 256 ]. These authors adopted a systems view and considered the sample’s network entropy, a measure of the signaling pathway promiscuity, which is computable from a sample’s genome-wide expression profile [ 257 , 258 ]. These authors also indicate the high level of causality in the pattern of gene expression and in the cellular network entropy, both in cancer and with a progression and increase in the metastatic cells.…”

Section: Notes On Thermodynamicsmentioning

confidence: 99%

Cancer Stem Cell Theory and the Warburg Effect, Two Sides of the Same Coin?

Pacini¹,

Borziani²

2014

IJMS

View full text Add to dashboard Cite

Over the last 100 years, many studies have been performed to determine the biochemical and histopathological phenomena that mark the origin of neoplasms. At the end of the last century, the leading paradigm, which is currently well rooted, considered the origin of neoplasms to be a set of genetic and/or epigenetic mutations, stochastic and independent in a single cell, or rather, a stochastic monoclonal pattern. However, in the last 20 years, two important areas of research have underlined numerous limitations and incongruities of this pattern, the hypothesis of the so-called cancer stem cell theory and a revaluation of several alterations in metabolic networks that are typical of the neoplastic cell, the so-called Warburg effect. Even if this specific “metabolic sign” has been known for more than 85 years, only in the last few years has it been given more attention; therefore, the so-called Warburg hypothesis has been used in multiple and independent surveys. Based on an accurate analysis of a series of considerations and of biophysical thermodynamic events in the literature, we will demonstrate a homogeneous pattern of the cancer stem cell theory, of the Warburg hypothesis and of the stochastic monoclonal pattern; this pattern could contribute considerably as the first basis of the development of a new uniform theory on the origin of neoplasms. Thus, a new possible epistemological paradigm is represented; this paradigm considers the Warburg effect as a specific “metabolic sign” reflecting the stem origin of the neoplastic cell, where, in this specific metabolic order, an essential reason for the genetic instability that is intrinsic to the neoplastic cell is defined.

show abstract

“…ApEn is applied in finance, physiology, medicine science and so on. The ApEn of the network reflects the unpredictability of the network and can be used to measure the possibility of the existence of unknown nodes in the network [4].…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Measurement of Basic Probability Assignment Integrity Based on Approximate Entropy in Evidence Theory

Zhan,

He,

et al. 2021

Preprint

View full text Add to dashboard Cite

Evidence theory is that the extension of probability can better deal with unknowns and inaccurate information. Uncertainty measurement plays a vital role in both evidence theory and probability theory. Approximate Entropy (ApEn) is proposed by Pincus to describe the irregularities of complex systems. The more irregular the time series, the greater the approximate entropy. The ApEn of the network represents the ability of a network to generate new nodes, or the possibility of undiscovered nodes. Through the association of network characteristics and basic probability assignment (BPA) , a measure of the uncertainty of BPA regarding completeness can be obtained. The main contribution of paper is to define the integrity of the basic probability assignment then the approximate entropy of the BPA is proposed to measure the uncertainty of the integrity of the BPA. The proposed method is based on the logical network structure to calculate the uncertainty of BPA in evidence theory. The uncertainty based on the proposed method represents the uncertainty of integrity of BPA and contributes to

show abstract

Approximate entropy of network parameters

Cited by 15 publications

References 42 publications

Visibility graphs of fractional Wu–Baleanu time series

Visibility graphs of fractional Wu–Baleanu time series

Cancer Stem Cell Theory and the Warburg Effect, Two Sides of the Same Coin?

Uncertainty Measurement of Basic Probability Assignment Integrity Based on Approximate Entropy in Evidence Theory

Contact Info

Product

Resources

About