Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Comparison of ancient and modern Chinese based on complex weighted networks.

ABSTRACT: In this study, we compare statistical properties of ancient and modern Chinese within the framework of weighted complex networks. We examine two language networks based on different Chinese versions of the Records of the Grand Historian. The comparative results show that Zipf's law holds and that both networks are scale-free and disassortative. The interactivity and connectivity of the two networks lead us to expect that the modern Chinese text would have more phrases than the ancient Chinese one. Furthermore, by considering some of the topological and weighted quantities, we find that expressions in ancient Chinese are briefer than in modern Chinese. These observations indicate that the two languages might have different linguistic mechanisms and combinatorial natures, which we attribute to the stylistic differences and evolution of written Chinese.

SUBMITTER: Cui X

PROVIDER: S-EPMC5681291 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Comparison of ancient and modern Chinese based on complex weighted networks.

Cui Xinru X Qi Jinxu J Tan Hao H Chen Feng F

PloS one 20171110 11

In this study, we compare statistical properties of ancient and modern Chinese within the framework of weighted complex networks. We examine two language networks based on different Chinese versions of the Records of the Grand Historian. The comparative results show that Zipf's law holds and that both networks are scale-free and disassortative. The interactivity and connectivity of the two networks lead us to expect that the modern Chinese text would have more phrases than the ancient Chinese on ...[more]

PMID: 29125870

Similar Datasets

Topological Strata of Weighted Complex Networks.

Project description:The statistical mechanical approach to complex networks is the dominant paradigm in describing natural and societal complex systems. The study of network properties, and their implications on dynamical processes, mostly focus on locally defined quantities of nodes and edges, such as node degrees, edge weights and -more recently- correlations between neighboring nodes. However, statistical methods quickly become cumbersome when dealing with many-body properties and do not capture the precise mesoscopic structure of complex networks. Here we introduce a novel method, based on persistent homology, to detect particular non-local structures, akin to weighted holes within the link-weight network fabric, which are invisible to existing methods. Their properties divide weighted networks in two broad classes: one is characterized by small hierarchically nested holes, while the second displays larger and longer living inhomogeneities. These classes cannot be reduced to known local or quasilocal network properties, because of the intrinsic non-locality of homological properties, and thus yield a new classification built on high order coordination patterns. Our results show that topology can provide novel insights relevant for many-body interactions in social and spatial networks. Moreover, this new method creates the first bridge between network theory and algebraic topology, which will allow to import the toolset of algebraic methods to complex systems.

| S-EPMC3689815 | biostudies-literature

Extracting the multiscale backbone of complex weighted networks.

Project description:A large number of complex systems find a natural abstraction in the form of weighted networks whose nodes represent the elements of the system and the weighted edges identify the presence of an interaction and its relative strength. In recent years, the study of an increasing number of large-scale networks has highlighted the statistical heterogeneity of their interaction pattern, with degree and weight distributions that vary over many orders of magnitude. These features, along with the large number of elements and links, make the extraction of the truly relevant connections forming the network's backbone a very challenging problem. More specifically, coarse-graining approaches and filtering techniques come into conflict with the multiscale nature of large-scale systems. Here, we define a filtering method that offers a practical procedure to extract the relevant connection backbone in complex multiscale networks, preserving the edges that represent statistically significant deviations with respect to a null model for the local assignment of weights to edges. An important aspect of the method is that it does not belittle small-scale interactions and operates at all scales defined by the weight distribution. We apply our method to real-world network instances and compare the obtained results with alternative backbone extraction techniques.

| S-EPMC2672499 | biostudies-literature

Ancient and modern environmental DNA.

Project description:DNA obtained from environmental samples such as sediments, ice or water (environmental DNA, eDNA), represents an important source of information on past and present biodiversity. It has revealed an ancient forest in Greenland, extended by several thousand years the survival dates for mainland woolly mammoth in Alaska, and pushed back the dates for spruce survival in Scandinavian ice-free refugia during the last glaciation. More recently, eDNA was used to uncover the past 50 000 years of vegetation history in the Arctic, revealing massive vegetation turnover at the Pleistocene/Holocene transition, with implications for the extinction of megafauna. Furthermore, eDNA can reflect the biodiversity of extant flora and fauna, both qualitatively and quantitatively, allowing detection of rare species. As such, trace studies of plant and vertebrate DNA in the environment have revolutionized our knowledge of biogeography. However, the approach remains marred by biases related to DNA behaviour in environmental settings, incomplete reference databases and false positive results due to contamination. We provide a review of the field.

| S-EPMC4275890 | biostudies-other

A weighted communicability measure applied to complex brain networks.

Project description:Recent advances in experimental neuroscience allow non-invasive studies of the white matter tracts in the human central nervous system, thus making available cutting-edge brain anatomical data describing these global connectivity patterns. Through magnetic resonance imaging, this non-invasive technique is able to infer a snapshot of the cortical network within the living human brain. Here, we report on the initial success of a new weighted network communicability measure in distinguishing local and global differences between diseased patients and controls. This approach builds on recent advances in network science, where an underlying connectivity structure is used as a means to measure the ease with which information can flow between nodes. One advantage of our method is that it deals directly with the real-valued connectivity data, thereby avoiding the need to discretize the corresponding adjacency matrix, i.e. to round weights up to 1 or down to 0, depending upon some threshold value. Experimental results indicate that the new approach is able to extract biologically relevant features that are not immediately apparent from the raw connectivity data.

| S-EPMC2658663 | biostudies-literature

Structural and Dynamics Comparison of Thermostability in Ancient, Modern, and Consensus Elongation Factor Tus.

Project description:Rationally engineering thermostability in proteins would create enzymes and receptors that function under harsh industrial applications. Several sequence-based approaches can generate thermostable variants of mesophilic proteins. To gain insight into the mechanisms by which proteins become more stable, we use structural and dynamic analyses to compare two popular approaches, ancestral sequence reconstruction (ASR) and the consensus method, used to generate thermostable variants of Elongation Factor Thermo-unstable (EF-Tu). We present crystal structures of ancestral and consensus EF-Tus, accompanied by molecular dynamics simulations aimed at probing the strategies employed to enhance thermostability. All proteins adopt crystal structures similar to extant EF-Tus, revealing no difference in average structure between the methods. Molecular dynamics reveals that ASR-generated sequences retain dynamic properties similar to extant, thermostable EF-Tu from Thermus aquaticus, while consensus EF-Tu dynamics differ from evolution-based sequences. This work highlights the advantage of ASR for engineering thermostability while preserving natural motions in multidomain proteins.

| S-EPMC5785943 | biostudies-literature

Comparison of observer based methods for source localisation in complex networks.

Project description:In recent years, research on methods for locating a source of spreading phenomena in complex networks has seen numerous advances. Such methods can be applied not only to searching for the "patient zero" in epidemics, but also finding the true sources of false or malicious messages circulating in the online social networks. Many methods for solving this problem have been established and tested in various circumstances. Yet, we still lack reviews that would include a direct comparison of efficiency of these methods. In this paper, we provide a thorough comparison of several observer-based methods for source localisation on complex networks. All methods use information about the exact time of spread arrival at a pre-selected group of vertices called observers. We investigate how the precision of the studied methods depends on the network topology, density of observers, infection rate, and observers' placement strategy. The direct comparison between methods allows for an informed choice of the methods for applications or further research. We find that the Pearson correlation based method and the method based on the analysis of multiple paths are the most effective in networks with synthetic or real topologies. The former method dominates when the infection rate is low; otherwise, the latter method takes over.

| S-EPMC8948209 | biostudies-literature

Reliable Multi-Fractal Characterization of Weighted Complex Networks: Algorithms and Implications.

Project description:Through an elegant geometrical interpretation, the multi-fractal analysis quantifies the spatial and temporal irregularities of the structural and dynamical formation of complex networks. Despite its effectiveness in unweighted networks, the multi-fractal geometry of weighted complex networks, the role of interaction intensity, the influence of the embedding metric spaces and the design of reliable estimation algorithms remain open challenges. To address these challenges, we present a set of reliable multi-fractal estimation algorithms for quantifying the structural complexity and heterogeneity of weighted complex networks. Our methodology uncovers that (i) the weights of complex networks and their underlying metric spaces play a key role in dictating the existence of multi-fractal scaling and (ii) the multi-fractal scaling can be localized in both space and scales. In addition, this multi-fractal characterization framework enables the construction of a scaling-based similarity metric and the identification of community structure of human brain connectome. The detected communities are accurately aligned with the biological brain connectivity patterns. This characterization framework has no constraint on the target network and can thus be leveraged as a basis for both structural and dynamic analysis of networks in a wide spectrum of applications.

| S-EPMC5548933 | biostudies-literature

A comparative analysis of link removal strategies in real complex weighted networks.

Project description:In this report we offer the widest comparison of links removal (attack) strategies efficacy in impairing the robustness of six real-world complex weighted networks. We test eleven different link removal strategies by computing their impact on network robustness by means of using three different measures, i.e. the largest connected cluster (LCC), the efficiency (Eff) and the total flow (TF). We find that, in most of cases, the removal strategy based on the binary betweenness centrality of the links is the most efficient to disrupt the LCC. The link removal strategies based on binary-topological network features are less efficient in decreasing the weighted measures of the network robustness (e.g. Eff and TF). Removing highest weight links first is the best strategy to decrease the efficiency (Eff) in most of the networks. Last, we found that the removal of a very small fraction of links connecting higher strength nodes or of highest weight does not affect the LCC but it determines a rapid collapse of the network efficiency Eff and the total flow TF. This last outcome raises the importance of both to adopt weighted measures of network robustness and to focus the analyses on network response to few link removals.

| S-EPMC7054356 | biostudies-literature

Mitochondrial phylogenomics of modern and ancient equids.

Project description:The genus Equus is richly represented in the fossil record, yet our understanding of taxonomic relationships within this genus remains limited. To estimate the phylogenetic relationships among modern horses, zebras, asses and donkeys, we generated the first data set including complete mitochondrial sequences from all seven extant lineages within the genus Equus. Bayesian and Maximum Likelihood phylogenetic inference confirms that zebras are monophyletic within the genus, and the Plains and Grevy's zebras form a well-supported monophyletic group. Using ancient DNA techniques, we further characterize the complete mitochondrial genomes of three extinct equid lineages (the New World stilt-legged horses, NWSLH; the subgenus Sussemionus; and the Quagga, Equus quagga quagga). Comparisons with extant taxa confirm the NWSLH as being part of the caballines, and the Quagga and Plains zebras as being conspecific. However, the evolutionary relationships among the non-caballine lineages, including the now-extinct subgenus Sussemionus, remain unresolved, most likely due to extremely rapid radiation within this group. The closest living outgroups (rhinos and tapirs) were found to be too phylogenetically distant to calibrate reliable molecular clocks. Additional mitochondrial genome sequence data, including radiocarbon dated ancient equids, will be required before revisiting the exact timing of the lineage radiation leading up to modern equids, which for now were found to have possibly shared a common ancestor as far as up to 4 Million years ago (Mya).

| S-EPMC3577844 | biostudies-literature

Cholera--modern pandemic disease of ancient lineage.

Project description:Cholera has affected humans for at least a millennium and persists as a major cause of illness and death worldwide, with recent epidemics in Zimbabwe (2008-2009) and Haiti (2010). Clinically, evidence exists of increasing severity of disease linked with emergence of atypical Vibrio cholerae organisms that have incorporated genetic material from classical biotype strains into an El Tor biotype background. A key element in transmission may be a recently recognized hyperinfectious phase, which persists for hours after passage in diarrheal feces. We propose a model of transmission in which environmental triggers (such as temperature) lead to increases in V. cholerae in environmental reservoirs, with spillover into human populations. However, once the microorganism is introduced into a human population, transmission occurs primary by "fast" transmission from person to person (taking advantage of the hyperinfectious state), without returning to the aquatic environment.

| S-EPMC3310593 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data