Effects of link perturbation on network modularity for community detections in complex network systems

2021 ◽  
pp. 2150214
Author(s):  
Dongyan Zhao ◽  
Jing Li ◽  
Zhongyuan Jiang
Keyword(s):  
Complex Network ◽  
Community Detection ◽  
Real World ◽  
Perturbation Methods ◽  
Random Perturbation ◽  
Network Structures ◽  
Network Systems ◽  
Network Modularity ◽  
The Impact

Community detection is of great significance in analyzing the network structures. However, real networks usually contain missing links and spurious interactions, which affect the accuracy of community detection results. In this paper, we aim to find out the regularity of the impact on community detection when links are deleted from or added to the network. To address this problem, we propose degree-related link perturbation (DRLP) methods for the tasks of both deleting and adding links, and the random perturbation methods are also be employed. Then, we evaluate the impact of perturbation methods on community detection and draw some conclusions. Finally, extensive experiments conducted on six real-world networks demonstrate the existence of the regularity. The perturbation of deleting and adding links can lead to continuous rise and decline of modularity, respectively, which is also instructive to change the results of community detection purposefully.

scholarly journals LIMITED RESOLUTION AND MULTIRESOLUTION METHODS IN COMPLEX NETWORK COMMUNITY DETECTION

2007 ◽  
Vol 07 (03) ◽  
pp. L209-L214 ◽  
Author(s):  
JUSSI M. KUMPULA ◽  
JARI SARAMÄKI ◽  
KIMMO KASKI ◽  
JÁNOS KERTÉSZ
Keyword(s):  
Simulated Annealing ◽  
Community Structure ◽  
Complex Network ◽  
Community Detection ◽  
Real World ◽  
Tuning Parameter ◽  
Challenging Problem ◽  
Resolution Limit ◽  
Network Community ◽  
Multiresolution Methods

Detecting community structure in real-world networks is a challenging problem. Recently, it has been shown that the resolution of methods based on optimizing a modularity measure or a corresponding energy is limited; communities with sizes below some threshold remain unresolved. One possibility to go around this problem is to vary the threshold by using a tuning parameter, and investigate the community structure at variable resolutions. Here, we analyze the resolution limit and multiresolution behavior for two different methods: a q-state Potts method proposed by Reichard and Bornholdt, and a recent multiresolution method by Arenas, Fernández, and Gómez. These methods are studied analytically, and applied to three test networks using simulated annealing.

On the Dynamics of Complex Network

2017 ◽  
Author(s):  
Chun-Lin Yang ◽  
C. Steve Suh
Keyword(s):  
Statistical Mechanics ◽  
Complex Network ◽  
Real World ◽  
Local Level ◽  
Structure Model ◽  
Statistical Entropy ◽  
Network Configuration ◽  
Visual Contact ◽  
Network Systems ◽  
Network Property

Controlling complex network systems is challenging because network systems are highly coupled by ensembles and behaving with uncertainty. A network is composed by nodes and edges. Edges serve as the connection between nodes to exchange state information and further achieve state consensus. Through edges, the dynamics of individual nodes at the local level intimately affects the network dynamics at the global level. As a following bird can occasionally lose visual contact with the target bird in a flock at any moment, the edge between two nodes in a real world network systems is not necessarily always intact. Contrary to common sense, these real-world networks are usually perfectly stable even when the edges between the nodes are unstable. This suggests that not only nodes are dynamical, edges are dynamical, too. Since the edges between the nodes are changing dynamically, network configuration is also dynamical. Further, edges need be defined and quantified so that the unstable connection behavior can be properly described. The paper explores the concepts of statistical mechanics and statistical entropy to address the particular need. Statistical mechanics describes the behavior of a mechanical system that has uncertain states. Statistical entropy on the other hand defines the distribution of the microstates by probability. Entropy provides a measure of the level of network integrity. With entropy, one can assign desired dynamics to the network to ensure desired network property. This work aims to construct a complex network structure model based on the edge dynamics. Coupled with node self-dynamic and consensus law, a general dynamical network model can be constructed.

scholarly journals Overlapping Community Detection Based on Membership Degree Propagation

Entropy ◽  
2020 ◽  
Vol 23 (1) ◽  
pp. 15
Author(s):  
Rui Gao ◽  
Shoufeng Li ◽  
Xiaohu Shi ◽  
Yanchun Liang ◽  
Dong Xu
Keyword(s):  
Complex Network ◽  
Community Detection ◽  
Real World ◽  
Detection Algorithm ◽  
Label Propagation ◽  
Computational Time ◽  
Membership Degree ◽  
Overlapping Community Detection ◽  
Overlapping Community ◽  
Real World Datasets

A community in a complex network refers to a group of nodes that are densely connected internally but with only sparse connections to the outside. Overlapping community structures are ubiquitous in real-world networks, where each node belongs to at least one community. Therefore, overlapping community detection is an important topic in complex network research. This paper proposes an overlapping community detection algorithm based on membership degree propagation that is driven by both global and local information of the node community. In the method, we introduce a concept of membership degree, which not only stores the label information, but also the degrees of the node belonging to the labels. Then the conventional label propagation process could be extended to membership degree propagation, with the results mapped directly to the overlapping community division. Therefore, it obtains the partition result and overlapping node identification simultaneously and greatly reduces the computational time. The proposed algorithm was applied to a synthetic Lancichinetti–Fortunato–Radicchi (LFR) dataset and nine real-world datasets and compared with other up-to-date algorithms. The experimental results show that our proposed algorithm is effective and outperforms the comparison methods on most datasets. Our proposed method significantly improved the accuracy and speed of the overlapping node prediction. It can also substantially alleviate the computational complexity of community structure detection in general.

scholarly journals Ripple-Spreading Network Model Optimization by Genetic Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Xiao-Bing Hu ◽  
Ming Wang ◽  
Mark S. Leeson
Keyword(s):  
Genetic Algorithm ◽  
Complex Network ◽  
Network Model ◽  
Real World ◽  
Network Models ◽  
Small World ◽  
Network Systems ◽  
Scale Free ◽  
Apply Genetic ◽  
Network Topologies

Small-world and scale-free properties are widely acknowledged in many real-world complex network systems, and many network models have been developed to capture these network properties. The ripple-spreading network model (RSNM) is a newly reported complex network model, which is inspired by the natural ripple-spreading phenomenon on clam water surface. The RSNM exhibits good potential for describing both spatial and temporal features in the development of many real-world networks where the influence of a few local events spreads out through nodes and then largely determines the final network topology. However, the relationships between ripple-spreading related parameters (RSRPs) of RSNM and small-world and scale-free topologies are not as obvious or straightforward as in many other network models. This paper attempts to apply genetic algorithm (GA) to tune the values of RSRPs, so that the RSNM may generate these two most important network topologies. The study demonstrates that, once RSRPs are properly tuned by GA, the RSNM is capable of generating both network topologies and therefore has a great flexibility to study many real-world complex network systems.

Narrative, Intertext and Allusion in the Qur'anic Presentation of Job

1999 ◽  
Vol 1 (1) ◽  
pp. 1-25 ◽  
Author(s):  
A. H. Johns
Keyword(s):  
Key Words ◽  
Complex Network ◽  
Key Words And Phrases ◽  
Divine Revelation ◽  
Western Tradition ◽  
Islamic Tradition ◽  
The Impact ◽  
The Way

Job (Ayyūb) is a byword for patience in the Islamic tradition, notwithstanding only six Qur'anic verses are devoted to him, four in Ṣād (vv.41-4), and two in al-Anbiyā' (vv.83-4), and he is mentioned on only two other occasions, in al-Ancām (v.84) and al-Nisā' (v.163). In relation to the space devoted to him, he could be accounted a ‘lesser’ prophet, nevertheless his significance in the Qur'an is unambiguous. The impact he makes is achieved in a number of ways. One is through the elaborate intertext transmitted from the Companions and Followers, and recorded in the exegetic tradition. Another is the way in which his role and charisma are highlighted by the prophets in whose company he is presented, and the shifting emphases of each of the sūras in which he appears. Yet another is the wider context created by these sūras in which key words and phrases actualize a complex network of echoes and resonances that elicit internal and transsūra associations focusing attention on him from various perspectives. The effectiveness of this presentation of him derives from the linguistic genius of the Qur'an which by this means triggers a vivid encounter with aspects of the rhythm of divine revelation no less direct than that of visual iconography in the Western Tradition.

1607-P: Real-World Evidence of the Impact of Obesity on Residual Teeth in the Japanese Population

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1607-P
Author(s):  
MAYU HAYASHI ◽  
KATSUTARO MORINO ◽  
KAYO HARADA ◽  
MIKI ISHIKAWA ◽  
ITSUKO MIYAZAWA ◽  
...  
Keyword(s):  
Real World ◽  
Japanese Population ◽  
Real World Evidence ◽  
The Impact

scholarly journals POS1121 DEMOGRAPHICS, COMORBIDITIES, AND RENAL FUNCTION OF UNCONTROLLED GOUT PATIENTS WHO RECEIVED PEGLOTICASE: FINDING FROM A LARGE US CLAIMS DATABASE

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 839.2-840
Author(s):  
C. Vesel ◽  
A. Morton ◽  
M. Francis-Sedlak ◽  
B. Lamoreaux
Keyword(s):  
Kidney Function ◽  
Real World ◽  
Randomized Clinical Trials ◽  
Small Subset ◽  
Phase 3 ◽  
Claims Database ◽  
Medical Diagnoses ◽  
Ckd Stage ◽  
Before And After ◽  
The Impact

Background:NHANES data indicate that approximately 9.2 million Americans have gout,1 with a small subset having uncontrolled disease.2 Pegloticase is a PEGylated recombinant uricase enzyme indicated for treating uncontrolled gout that markedly reduces serum uric acid levels (sUA)3 and resolves tophi in treatment responders.4 Despite pegloticase availability in the US for many years, real world demographics of pegloticase users in the treatment of uncontrolled gout have not been previously reported in a population-based cohort.Objectives:This study utilized a large US claims database to examine demographics and co-morbidities of uncontrolled gout patients treated with pegloticase. Kidney function before and after pegloticase treatment and concomitant therapy with immunomodulators were also examined.Methods:The TriNetX Diamond database includes de-identified data from 4.3 million US patients with gout (as of September 2019), including demographics, medical diagnoses, laboratory values, procedures (e.g. infusions, surgeries), and pharmacy data. Patients who had received ≥1 pegloticase infusion were included in these analyses. The number of infusions was evaluated for a subgroup of patients who were in the database ≥3 months before and ≥2 years after the first pegloticase infusion (i.e. first infusion prior to September 2017) to ensure only complete courses of therapy were captured. In this subpopulation, kidney function before and after pegloticase therapy was examined, along with the presence of immunomodulation prescriptions (methotrexate, mycophenolate mofetil, azathioprine, leflunomide) within 60 days prior to and 14 days after the first pegloticase infusion.Results:1494 patients treated with pegloticase were identified. Patients were 63.1 ± 14.0 years of age (range: 23–91), mostly male (82%), and white (76%). Mean sUA prior to pegloticase was 8.7 ± 2.4 mg/dL (n=50), indicating uncontrolled gout in the identified population. The most commonly reported comorbidities were chronic kidney disease (CKD, 48%), essential hypertension (71%), type 2 diabetes (39%), and cardiovascular disease (38%), similar to pegloticase pivotal Phase 3 trial populations. In patients with pre-therapy kidney function measures (n=134), pre-treatment eGFR averaged 61.2 ± 25.7 ml/min/1.73 m2, with 44% having Stage 3-5 CKD. In patients with complete therapy course capture and pre- and post-therapy eGFR measures (n=48), kidney function remained stable (change in eGFR: -2.9 ± 18.2 ml/min/1.73 m2) and CKD stage remained the same or improved in 81% of patients. In 791 patients with complete treatment course capture, patients had received 8.7 ± 13.8 infusions (median: 3, IQR: 2-10). Of these, 189 (24%) patients received only 1 pegloticase infusion and 173 (22%) received ≥12 infusions. As the data cut-off for this analysis pre-dated emerging data on the use of immunomodulation as co-therapy, only 19 of 791 (2%) patients received immunomodulation co-therapy with pegloticase.Conclusion:This relatively large group of patients with uncontrolled gout treated with pegloticase had similar patient characteristics of those studied in the phase 3 randomized clinical trials. Patients with uncontrolled gout are significantly burdened with systemic co-morbid diseases. The majority of patients had stable or improved kidney function following pegloticase treatment. As these results reflect patients initiating treatment prior to 2018, before co-treatment with immunomodulation was introduced, this cohort only included a small percentage of patients who were co-treated with an immunomodulator. Future studies using more current datasets are needed to evaluate real world outcomes in patients treated with pegloticase/immunomodulator co-therapy and to evaluate the impact of systemic co-morbid diseases.References:[1]Chen-Xu M, et al. Arthritis Rheumatol 2019 71:991-999.[2]Fels E, Sundy JS. Curr Opin Rheumatol 2008;20:198-202.[3]Sundy J, et al. JAMA 2011;306:711-720.[4]Mandell BF, et al. Arthritis Res Ther 2018;20:286.Disclosure of Interests:Claudia Vesel Shareholder of: Horizon Therapeutics plc, Employee of: Horizon Therapeutics plc, Allan Morton Speakers bureau: Sanofi, Amgen, and Horizon, Megan Francis-Sedlak Shareholder of: Horizon Therapeutics plc, Employee of: Horizon Therapeutics plc, Brian LaMoreaux Shareholder of: Horizon Therapeutics plc, Employee of: Horizon Therapeutics plc.

PP469 From Theory To Practice: Which Value Framework Is Applied For Onco-Hematology Therapies In Italy? A 5-year Retrospective Analysis

2020 ◽  
Vol 36 (S1) ◽  
pp. 37-37
Author(s):  
Americo Cicchetti ◽  
Rossella Di Bidino ◽  
Entela Xoxi ◽  
Irene Luccarini ◽  
Alessia Brigido
Keyword(s):  
Real World ◽  
Ad Hoc ◽  
Grey Literature ◽  
National Level ◽  
Pharmaceutical Products ◽  
European Medicines Agency ◽  
The Real ◽  
R Process ◽  
The One ◽  
The Impact

IntroductionDifferent value frameworks (VFs) have been proposed in order to translate available evidence on risk-benefit profiles of new treatments into Pricing & Reimbursement (P&R) decisions. However limited evidence is available on the impact of their implementation. It's relevant to distinguish among VFs proposed by scientific societies and providers, which usually are applicable to all treatments, and VFs elaborated by regulatory agencies and health technology assessment (HTA), which focused on specific therapeutic areas. Such heterogeneity in VFs has significant implications in terms of value dimension considered and criteria adopted to define or support a price decision.MethodsA literature research was conducted to identify already proposed or adopted VF for onco-hematology treatments. Both scientific and grey literature were investigated. Then, an ad hoc data collection was conducted for multiple myeloma; breast, prostate and urothelial cancer; and Non Small Cell Lung Cancer (NSCLC) therapies. Pharmaceutical products authorized by European Medicines Agency from January 2014 till December 2019 were identified. Primary sources of data were European Public Assessment Reports and P&R decision taken by the Italian Medicines Agency (AIFA) till September 2019.ResultsThe analysis allowed to define a taxonomy to distinguish categories of VF relevant to onco-hematological treatments. We identified the “real-world” VF that emerged given past P&R decisions taken at the Italian level. Data was collected both for clinical and economical outcomes/indicators, as well as decisions taken on innovativeness of therapies. Relevant differences emerge between the real world value framework and the one that should be applied given the normative framework of the Italian Health System.ConclusionsThe value framework that emerged from the analysis addressed issues of specific aspects of onco-hematological treatments which emerged during an ad hoc analysis conducted on treatment authorized in the last 5 years. The perspective adopted to elaborate the VF was the one of an HTA agency responsible for P&R decisions at a national level. Furthermore, comparing a real-world value framework with the one based on the general criteria defined by the national legislation, our analysis allowed identification of the most critical point of the current national P&R process in terms ofsustainability of current and future therapies as advance therapies and agnostic-tumor therapies.

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