Subjects -> COMPUTER SCIENCE (Total: 2313 journals)
    - ANIMATION AND SIMULATION (33 journals)
    - ARTIFICIAL INTELLIGENCE (133 journals)
    - AUTOMATION AND ROBOTICS (116 journals)
    - CLOUD COMPUTING AND NETWORKS (75 journals)
    - COMPUTER ARCHITECTURE (11 journals)
    - COMPUTER ENGINEERING (12 journals)
    - COMPUTER GAMES (23 journals)
    - COMPUTER PROGRAMMING (25 journals)
    - COMPUTER SCIENCE (1305 journals)
    - COMPUTER SECURITY (59 journals)
    - DATA BASE MANAGEMENT (21 journals)
    - DATA MINING (50 journals)
    - E-BUSINESS (21 journals)
    - E-LEARNING (30 journals)
    - ELECTRONIC DATA PROCESSING (23 journals)
    - IMAGE AND VIDEO PROCESSING (42 journals)
    - INFORMATION SYSTEMS (109 journals)
    - INTERNET (111 journals)
    - SOCIAL WEB (61 journals)
    - SOFTWARE (43 journals)
    - THEORY OF COMPUTING (10 journals)

COMPUTER SCIENCE (1305 journals)

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Theory in Biosciences
Journal Prestige (SJR): 0.557
Citation Impact (citeScore): 1
Number of Followers: 0  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1611-7530 - ISSN (Online) 1431-7613
Published by Springer-Verlag Homepage  [2468 journals]
  • Rethinking life and predicting its origin

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      Abstract: Abstract The definition, origin and recreation of life remain elusive. As others have suggested, only once we put life into reductionist physical terms will we be able to solve those questions. To that end, this work proposes the phenomenon of life to be the product of two dissipative mechanisms. From them, one characterises extant biological life and deduces a testable scenario for its origin. The proposed theory of life allows its replication, reinterprets ecological evolution and creates new constraints on the search for life.
      PubDate: 2024-06-26
       
  • Application of network pharmacology in synergistic action of Chinese
           herbal compounds

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      Abstract: Abstract Herbal medicines are frequently blended in the form of multi-drug combinations primarily based on the precept of medicinal compatibility, to achieve the purpose of treating diseases. However, due to the lack of appropriate techniques and the multi-component and multi-target nature of Chinese medicine compounding, it is tough to explain how the drugs interact with each other. As a rising discipline, cyber pharmacology has formed a new approach characterized by using holistic and systematic “network targets” via the cross-fertilization of computer technology, bioinformatics, and different multidisciplinary disciplines. It can broadly screen the active ingredients of traditional Chinese medicine, enhance the effective utilization of drugs, and elucidate the mechanism of drug action. We will overview the principles of Chinese medicine compounding and dispensing, the research methods of network pharmacology, and the software of network pharmacology in the lookup of compounded Chinese medicines, aiming to supply thoughts for the better application of network pharmacology in the research of Chinese medicines.
      PubDate: 2024-06-18
       
  • Prioritizing cervical cancer candidate genes using chaos game and
           fractal-based time series approach

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      Abstract: Abstract Cervical cancer is one of the most severe threats to women worldwide and holds fourth rank in lethality. It is estimated that 604, 127 cervical cancer cases have been reported in 2020 globally. With advancements in high throughput technologies and bioinformatics, several cervical candidate genes have been proposed for better therapeutic strategies. In this paper, we intend to prioritize the candidate genes that are involved in cervical cancer progression through a fractal time series-based cross-correlations approach. we apply the chaos game representation theory combining a two-dimensional multifractal detrended cross-correlations approach among the known and candidate genes involved in cervical cancer progression to prioritize the candidate genes. We obtained 16 candidate genes that showed cross-correlation with known cancer genes. Functional enrichment analysis of the candidate genes shows that they involve GO terms: biological processes, cell–cell junction assembly, cell–cell junction organization, regulation of cell shape, cortical actin cytoskeleton organization, and actomyosin structure organization. KEGG pathway analysis revealed genes’ role in Rap1 signaling pathway, ErbB signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, mTOR signaling pathway, Acute myeloid leukemia, chronic myeloid leukemia, Breast cancer, Thyroid cancer, Bladder cancer, and Gastric cancer. Further, we performed survival analysis and prioritized six genes CDH2, PAIP1, BRAF, EPB41L3, OSMR, and RUNX1 as potential candidate genes for cervical cancer that has a crucial role in tumor progression. We found that our study through this integrative approach an efficient tool and paved a new way to prioritize the candidate genes and these genes could be evaluated experimentally for potential validation. We suggest this may be useful in analyzing the nucleotide sequences and protein sequences for clustering, classification, class affiliation, etc.
      PubDate: 2024-05-28
       
  • The bubble theory: exploring the transition from first replicators to
           cells and viruses in a landscape-based scenario

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      Abstract: Abstract This study proposes a landscape-based scenario for the origin of viruses and cells, focusing on the adaptability of preexisting replicons from the RNP (ribonucleoprotein) world. The scenario postulates that life emerged in a subterranean “warm little pond” where organic matter accumulated, resulting in a prebiotic soup rich in nucleotides, amino acids, and lipids, which served as nutrients for the first self-replicating entities. Over time, the RNA world, followed by the RNP world, came into existence. Replicators/replicons, along with the nutritious soup from the pond, were washed out into the river and diluted. Lipid bubbles, enclosing organic matter, provided the last suitable environment for replicons to replicate. Two survival strategies emerged under these conditions: cell-like structures that obtained nutrients by merging with new bubbles, and virus-like entities that developed various techniques to transmit themselves to fresh bubbles. The presented hypothesis provides the possibility for the common origin of cells and viruses on rocky worlds hosting liquid water, like Earth.
      PubDate: 2024-05-09
       
  • Rethinking some roots of ecosystem approach in aquatic ecology: between
           the food cycle and lake metabolism

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      Abstract: Abstract The present study provides new insight into the key aspects of the early formative period of the ecosystem concept in aquatic ecology. Raymond Lindeman’s trophodynamics is known to be a starting point for the development of the modern concept of ecosystem. The trophodynamic approach in ecology was proposed by Lindeman in his widely cited paper of 1942. Lindeman’s views are analyzed in comparison with the contemporary production studies in aquatic ecology. It is shown that a similar theoretical system has been proposed in the USSR at the end of the 1930s by Georgiy G. Vinberg. He introduced the concept of biotic balance based on the wide appraisal of the dark and light bottles method. The study shows that both Lindeman’s trophodynamics and Vinberg’s concept of biotic balance relied on an energy-based approach in considering the wholeness of a water body. The two scientists, however, differed in several important aspects concerning the interpretation of the role of living organisms. The holistic interpretation of ecosystem by Lindeman and Vinberg can be seen as part of the dilemma between physicalism and organicism. At the same time, the main emphasis in the concepts of both Vinberg and Lindemann was on the primary production component, a feature that was common to the first holistic systems in production hydrobiology (e.g., E. Naumann’s regional limnology). It is clear that modern problems of aquatic ecology should be addressed from the perspective of the organismocentric understanding of the ecosystem, but undoubtedly at the new level of development of this view.
      PubDate: 2024-04-26
      DOI: 10.1007/s12064-024-00416-5
       
  • Mathematical analysis of a modified Volterra-Leslie chemostat Model

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      Abstract: Abstract In this paper, we investigate the asymptotic behavior of a modified chemostat model. We first demonstrate the existence of equilibria. Then, we present a mathematical analysis for the model, the invariance, the positivity, the persistence of the solutions, and the asymptotic global stability of the interior equilibrium. Some numerical simulations are carried out to illustrate the main results.
      PubDate: 2024-04-09
      DOI: 10.1007/s12064-024-00415-6
       
  • Dynamics of neural fields with exponential temporal kernel

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      Abstract: Abstract We consider the standard neural field equation with an exponential temporal kernel. We analyze the time-independent (static) and time-dependent (dynamic) bifurcations of the equilibrium solution and the emerging spatiotemporal wave patterns. We show that an exponential temporal kernel does not allow static bifurcations such as saddle-node, pitchfork, and in particular, static Turing bifurcations. However, the exponential temporal kernel possesses the important property that it takes into account the finite memory of past activities of neurons, which Green’s function does not. Through a dynamic bifurcation analysis, we give explicit bifurcation conditions. Hopf bifurcations lead to temporally non-constant, but spatially constant solutions, but Turing–Hopf bifurcations generate spatially and temporally non-constant solutions, in particular, traveling waves. Bifurcation parameters are the coefficient of the exponential temporal kernel, the transmission speed of neural signals, the time delay rate of synapses, and the ratio of excitatory to inhibitory synaptic weights.
      PubDate: 2024-03-09
      DOI: 10.1007/s12064-024-00414-7
       
  • Behavioral selection in structured populations

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      Abstract: Abstract The multilevel model of behavioral selection (MLBS) by Borgstede and Eggert (Behav Process 186:104370. 10.1016/j.beproc.2021.104370, 2021) provides a formal framework that integrates reinforcement learning with natural selection using an extended Price equation. However, the MLBS is so far only formulated for homogeneous populations, thereby excluding all sources of variation between individuals. This limitation is of primary theoretical concern because any application of the MLBS to real data requires to account for variation between individuals. In this paper, I extend the MLBS to account for inter-individual variation by dividing the population into homogeneous sub-populations and including class-specific reproductive values as weighting factors for an individual’s evolutionary fitness. The resulting formalism closes the gap between the theoretical underpinnings of behavioral selection and the application of the theory to empirical data, which naturally includes inter-individual variation. Furthermore, the extended MLBS is used to establish an explicit connection between the dynamics of learning and the maximization of individual fitness. These results expand the scope of the MLBS as a general theoretical framework for the quantitative analysis of learning and evolution.
      PubDate: 2024-03-05
      DOI: 10.1007/s12064-024-00413-8
       
  • Optimal dispersal and diffusion-enhanced robustness in two-patch
           metapopulations: origin’s saddle-source nature matters

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      Abstract: Abstract A two-patch logistic metapopulation model is investigated both analytically and numerically focusing on the impact of dispersal on population dynamics. First, the dependence of the global dynamics on the stability type of the full extinction equilibrium point is tackled. Then, the behaviour of the total population with respect to the dispersal is studied analytically. Our findings demonstrate that diffusion plays a crucial role in the preservation of both subpopulations and the full metapopulation under the presence of stochastic perturbations. At low diffusion, the origin is a repulsor, causing the orbits to flow nearly parallel to the axes, risking stochastic extinctions. Higher diffusion turns the repeller into a saddle point. Orbits then quickly converge to the saddle’s unstable manifold, reducing extinction chances. This change in the vector field enhances metapopulation robustness. On the other hand, the well-known fact that asymmetric conditions on the patches is beneficial for the total population is further investigated. This phenomenon has been studied in previous works for large enough or small enough values of the dispersal. In this work, we complete the theory for all values of the dispersal. In particular, we derive analytically a formula for the optimal value of the dispersal that maximizes the total population.
      PubDate: 2024-02-21
      DOI: 10.1007/s12064-023-00411-2
       
  • Modeling stress-induced responses: plasticity in continuous state space
           and gradual clonal evolution

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      Abstract: Abstract Mathematical models of cancer and bacterial evolution have generally stemmed from a gene-centric framework, assuming clonal evolution via acquisition of resistance-conferring mutations and selection of their corresponding subpopulations. More recently, the role of phenotypic plasticity has been recognized and models accounting for phenotypic switching between discrete cell states (e.g., epithelial and mesenchymal) have been developed. However, seldom do models incorporate both plasticity and mutationally driven resistance, particularly when the state space is continuous and resistance evolves in a continuous fashion. In this paper, we develop a framework to model plastic and mutational mechanisms of acquiring resistance in a continuous gradual fashion. We use this framework to examine ways in which cancer and bacterial populations can respond to stress and consider implications for therapeutic strategies. Although we primarily discuss our framework in the context of cancer and bacteria, it applies broadly to any system capable of evolving via plasticity and genetic evolution.
      PubDate: 2024-01-30
      DOI: 10.1007/s12064-023-00410-3
       
  • Speciation, natural selection, and networks: three historians versus
           theoretical population geneticists

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      Abstract: Abstract In 1913, the geneticist William Bateson called for a halt in studies of genetic phenomena until evolutionary fundamentals had been sufficiently addressed at the molecular level. Nevertheless, in the 1960s, the theoretical population geneticists celebrated a “modern synthesis” of the teachings of Mendel and Darwin, with an exclusive role for natural selection in speciation. This was supported, albeit with minor reservations, by historians Mark Adams and William Provine, who taught it to generations of students. In subsequent decades, doubts were raised by molecular biologists and, despite the deep influence of various mentors, Adams and Provine noted serious anomalies and began to question traditional “just-so-stories.” They were joined in challenging the genetic orthodoxy by a scientist-historian, Donald Forsdyke, who suggested that a “collective variation” postulated by Darwin’s young research associate, George Romanes, and a mysterious “residue” postulated by Bateson, might relate to differences in short runs of DNA bases (oligonucleotides). The dispute between a small network of historians and a large network of geneticists can be understood in the context of national politics. Contrasts are drawn between democracies, where capturing the narrative makes reversal difficult, and dictatorships, where overthrow of a supportive dictator can result in rapid reversal.
      PubDate: 2024-01-29
      DOI: 10.1007/s12064-024-00412-9
       
  • Thomas S. Kuhn: key to a better understanding of the extended evolutionary
           synthesis

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      Abstract: Abstract In recent years, some scholars have explicitly questioned the desirability or utility of applying the classical and “old-fashioned” theories of scientific change by the likes of Karl Popper and Thomas S. Kuhn to the question of the precise nature and significance of the extended evolutionary synthesis (EES). Supposedly, these twentieth-century philosophers are completely irrelevant for a better understanding of this new theoretical framework for the study of evolution. Here, it will be argued that the EES can be fruitfully interpreted in terms of, as yet, insufficiently considered or even overlooked elements from Kuhn’s theory. First, in his original, historical philosophy of science, Kuhn not only distinguished between small and big scientific revolutions, he also pointed out that paradigms can be extended and reformulated. In contrast with what its name suggests, the mainstream EES can be interpreted as a Kuhnian reformulation of modern evolutionary theory. Second, it has, as yet, also been overlooked that the EES can be interpreted in terms of Kuhn’s later, tentative evolutionary philosophy of science. With the EES, an old dichotomy in evolutionary biology is maybe being formalized and institutionalized.
      PubDate: 2023-11-17
      DOI: 10.1007/s12064-023-00409-w
       
  • Normalizing need not be the norm: count-based math for analyzing
           single-cell data

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      Abstract: Counting transcripts of mRNA are a key method of observation in modern biology. With advances in counting transcripts in single cells (single-cell RNA sequencing or scRNA-seq), these data are routinely used to identify cells by their transcriptional profile, and to identify genes with differential cellular expression. Because the total number of transcripts counted per cell can vary for technical reasons, the first step of many commonly used scRNA-seq workflows is to normalize by sequencing depth, transforming counts into proportional abundances. The primary objective of this step is to reshape the data such that cells with similar biological proportions of transcripts end up with similar transformed measurements. But there is growing concern that normalization and other transformations result in unintended distortions that hinder both analyses and the interpretation of results. This has led to an intense focus on optimizing methods for normalization and transformation of scRNA-seq data. Here, we take an alternative approach, by avoiding normalization and transformation altogether. We abandon the use of distances to compare cells, and instead use a restricted algebra, motivated by measurement theory and abstract algebra, that preserves the count nature of the data. We demonstrate that this restricted algebra is sufficient to draw meaningful and practical comparisons of gene expression through the use of the dot product and other elementary operations. This approach sidesteps many of the problems with common transformations, and has the added benefit of being simpler and more intuitive. We implement our approach in the package countland, available in python and R.
      PubDate: 2023-11-10
      DOI: 10.1007/s12064-023-00408-x
       
  • On a population model with density dependence and Allee effect

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      Abstract: Abstract We study the dynamics of a discrete model with two different stages of the population, the pre-adult stage governed by a Beverton–Holt-type map and the adult stage by a \(\gamma\) -Ricker map. The composition of both maps gives the dynamics. The existence of the Allee effect is easily observed. We check that the model can evolve from a sure extinction to complicated dynamics. The presence of an almost sure extinction is proved to exist when the dynamical complexity is the highest possible.
      PubDate: 2023-10-02
      DOI: 10.1007/s12064-023-00407-y
       
  • Matrix stability and bifurcation analysis by a network-based approach

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      Abstract: Abstract In this paper, we develop a network-based methodology to investigate the problems related to matrix stability and bifurcations in nonlinear dynamical systems. By matching a matrix with a network, i.e., interaction graph, we propose a new network-based matrix analysis method by proving a theorem about matrix determinant under which matrix stability can be considered in terms of feedback loops. Especially, the approach can tell us how a node, a path, or a feedback loop in the interaction graph affects matrix stability. In addition, the roles played by a node, a path, or a feedback loop in determining bifurcations in nonlinear dynamical systems can also be revealed. Therefore, the approach can help us to screen optimal node or node combinations. By perturbing them, unstable matrices can be stabilized more efficiently or bifurcations can be induced more easily to realize desired state transitions. To illustrate feasibility and efficiency of the approach, some simple matrices are used to show how single or combinatorial perturbations affect matrix stability and induce bifurcations. In addition, the main idea is also illustrated through a biological problem related to T cell development with three nodes: TCF-1, GATA3, and PU.1, which can be considered to be a three-variable nonlinear dynamical system. The approach is especially helpful in understanding crucial roles of single or molecule combinations in biomolecular networks. The approach presented here can be expected to analyze other biological networks related to cell fate transitions and systematic perturbation strategy selection.
      PubDate: 2023-09-27
      DOI: 10.1007/s12064-023-00405-0
       
  • Evolution by habit: Peirce, Lamarck, and teleology in biology

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      Abstract: Abstract In our paper, we analyse the relationship of the evolutionary philosophy of Charles Sanders Peirce to Lamarckian natural philosophy and link it to concepts of teleology, focusing especially on Aristotelian and Peircean conceptions of the final cause. Peirce commented on evolution in many of his writings, especially in 1891–1893 in essays such as ‘Evolutionary Love’ (1893) or ‘Man’s Glassy Essence’ (1892). After introducing the three types of evolution distinguished by Peirce, we compare Peirce’s and Lamarck’s views on evolution, habit, and teleology. From a synthesis of concepts formulated by Peirce, Aristotle, nineteenth-century neo-Lamarckians, and current knowledge regarding epigenetics, there should emerge our own concept of biological teleology unburdened by panpsychism, subjective intentions, or determinism. We believe it could be a concept acceptable to current biology.
      PubDate: 2023-09-25
      DOI: 10.1007/s12064-023-00406-z
       
  • Myths of past biases and progress in biology

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      Abstract: Abstract Two ideas are popular among biologists. The first idea is concerned with the biased nature of biology, especially the idea that biologists have overemphasized the importance of competition in the past. The second idea is concerned with progress in correcting for biases, namely, that the biased nature of biology decreases with time. To test these ideas, data on the popularity of interaction topics, such as competition, predation, and mutualism, was collected from articles published in biology journals. Research biases should be visible in publication data as systematic over- and underemphases regarding the popularity of alternative, viable research topics. Were the two ideas correct, data should show that the popularity of a historically dominant topic(s) diminishes with time, whereas the popularity of historically marginal, alternative topics increases with time. The data show that the two ideas are false. According to publication data, the biased nature of biology increases with time, which is a sign of regress rather than progress in biology.
      PubDate: 2023-09-23
      DOI: 10.1007/s12064-023-00403-2
       
  • A biosemiotic interpretation of certain genital morphological structures
           in the spiders Dysdera erythrina and Dysdera crocata (Araneae: Dysderidae)
           

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      Abstract: Abstract A biosemiotic approach to the interpretation of morphological data is apt to highlight morphological traits that have hitherto gone unnoticed for their crucial roles in intraspecific sign interpretation and communication processes. Examples of such traits include specific genital structures found in the haplogyne spiders Dysdera erythrina (Walckenaer 1802) and Dysdera crocata (Koch 1838). In both D. erythrina and D. crocata, the distal sclerite of the male bulb and the anterior diverticulum of the female endogyne exhibit a striking, previously unreported correspondence in size and shape, allowing for a precise match between these structures during copulation. In D. erythrina, the sclerite at the tip of the bulb and the anterior diverticulum are semi-circular in shape, whereas in D. crocata they are rectangular. From the perspective of biosemiotics, which studies the production and interpretation of signs and codes in living systems, these structures are considered the morphological zones of an intraspecific sign interpretation process. This process constitutes one of the necessary prerequisites for sperm transfer and the achievement of fertilization. Therefore, these morphological elements deserve particular attention as they hold higher taxonomic value compared to morphological traits of the bulb for which a relevant role in mating and fertilization has not been proven. Thus, an approach to species delimitation based on biosemiotics, with its specific evaluation of morphological structures, provides new insights for the multidisciplinary endeavour of modern integrative taxonomy.
      PubDate: 2023-09-13
      DOI: 10.1007/s12064-023-00404-1
       
  • MLACNN: an attention mechanism-based CNN architecture for predicting
           genome-wide DNA methylation

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      Abstract: Abstract Methylation is an important epigenetic regulation of methylation genes that plays a crucial role in regulating biological processes. While traditional methods for detecting methylation in biological experiments are constantly improving, the development of artificial intelligence has led to the emergence of deep learning and machine learning methods as a new trend. However, traditional machine learning-based methods rely heavily on manual feature extraction, and most deep learning methods for studying methylation extract fewer features due to their simple network structures. To address this, we propose a bottomneck network based on an attention mechanism and use new methods to ensure that the deep network can learn more effective features while minimizing overfitting. This approach enables the model to learn more features from nucleotide sequences and make better predictions of methylation. The model uses three coding methods to encode the original DNA sequence and then applies feature fusion based on attention mechanisms to obtain the best fusion method. Our results demonstrate that MLACNN outperforms previous methods and achieves more satisfactory performance.
      PubDate: 2023-08-30
      DOI: 10.1007/s12064-023-00402-3
       
  • Clustering systems of phylogenetic networks

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      Abstract: Abstract Rooted acyclic graphs appear naturally when the phylogenetic relationship of a set X of taxa involves not only speciations but also recombination, horizontal transfer, or hybridization that cannot be captured by trees. A variety of classes of such networks have been discussed in the literature, including phylogenetic, level-1, tree-child, tree-based, galled tree, regular, or normal networks as models of different types of evolutionary processes. Clusters arise in models of phylogeny as the sets \({{\,\mathrm{\texttt{C}}\,}}(v)\) of descendant taxa of a vertex v. The clustering system \(\mathscr {C}_N\) comprising the clusters of a network N conveys key information on N itself. In the special case of rooted phylogenetic trees, T is uniquely determined by its clustering system \(\mathscr {C}_T\) . Although this is no longer true for networks in general, it is of interest to relate properties of N and \(\mathscr {C}_N\) . Here, we systematically investigate the relationships of several well-studied classes of networks and their clustering systems. The main results are correspondences of classes of networks and clustering systems of the following form: If N is a network of type \(\mathbb {X}\) , then \(\mathscr {C}_N\) satisfies \(\mathbb {Y}\) , and conversely if \(\mathscr {C}\) is a clustering system satisfying \(\mathbb {Y},\) then there is network N of type \(\mathbb {X}\) such that \(\mathscr {C}\subseteq \mathscr {C}_N\) .This, in turn, allows us to investigate the mutual dependencies between the distinct types of networks in much detail.
      PubDate: 2023-08-12
      DOI: 10.1007/s12064-023-00398-w
       
 
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  Subjects -> COMPUTER SCIENCE (Total: 2313 journals)
    - ANIMATION AND SIMULATION (33 journals)
    - ARTIFICIAL INTELLIGENCE (133 journals)
    - AUTOMATION AND ROBOTICS (116 journals)
    - CLOUD COMPUTING AND NETWORKS (75 journals)
    - COMPUTER ARCHITECTURE (11 journals)
    - COMPUTER ENGINEERING (12 journals)
    - COMPUTER GAMES (23 journals)
    - COMPUTER PROGRAMMING (25 journals)
    - COMPUTER SCIENCE (1305 journals)
    - COMPUTER SECURITY (59 journals)
    - DATA BASE MANAGEMENT (21 journals)
    - DATA MINING (50 journals)
    - E-BUSINESS (21 journals)
    - E-LEARNING (30 journals)
    - ELECTRONIC DATA PROCESSING (23 journals)
    - IMAGE AND VIDEO PROCESSING (42 journals)
    - INFORMATION SYSTEMS (109 journals)
    - INTERNET (111 journals)
    - SOCIAL WEB (61 journals)
    - SOFTWARE (43 journals)
    - THEORY OF COMPUTING (10 journals)

COMPUTER SCIENCE (1305 journals)

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Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
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