Catalytic and binding sites prediction in globular proteins through discrete Markov chains and network centrality measures

2021 ◽  
Author(s):  
Gabriel Eloy Aguilar-Pineda ◽  
Luis Olivares-Quiroz
Keyword(s):  
Markov Chains ◽  
Binding Sites ◽  
Globular Proteins ◽  
Centrality Measures ◽  
Network Centrality

Comparison and Application of Metrics That Define the Components Modularity in Complex Products

2008 ◽  
Author(s):  
Qi D. Van Eikema Hommes
Keyword(s):  
Social Network ◽  
Centrality Measures ◽  
Software Systems ◽  
Network Centrality ◽  
Good Pair ◽  
Centrality Metrics ◽  
The Social ◽  
Social Network Centrality ◽  
Sample Test

As the content and variety of technology increases in automobiles, the complexity of the system increases as well. Decomposing systems into modules is one of the ways to manage and reduce system complexity. This paper surveys and compares a number of state-of-art components modularity metrics, using 8 sample test systems. The metrics include Whitney Index (WI), Change Cost (CC), Singular value Modularity Index (SMI), Visibility-Dependency (VD) plot, and social network centrality measures (degree, distance, bridging). The investigation reveals that WI and CC form a good pair of metrics that can be used to assess component modularity of a system. The social network centrality metrics are useful in identifying areas of architecture improvements for a system. These metrics were further applied to two actual vehicle embedded software systems. The first system is going through an architecture transformation. The metrics from the old system revealed the need for the improvements. The second system was recently architected, and the metrics values showed the quality of the architecture as well as areas for further improvements.

scholarly journals Identifying key papers within a journal via network centrality measures

2016 ◽  
Vol 107 (3) ◽  
pp. 1005-1020 ◽  
Author(s):  
Saikou Y. Diallo ◽  
Christopher J. Lynch ◽  
Ross Gore ◽  
Jose J. Padilla
Keyword(s):  
Centrality Measures ◽  
Network Centrality

scholarly journals Machine Learning in Network Centrality Measures

2019 ◽  
Vol 51 (5) ◽  
pp. 1-32 ◽  
Author(s):  
Felipe Grando ◽  
Lisandro Z. Granville ◽  
Luis C. Lamb
Keyword(s):  
Machine Learning ◽  
Centrality Measures ◽  
Network Centrality

scholarly journals Predicting dengue importation into Europe, using machine learning and model-agnostic methods

2019 ◽  
Author(s):  
Donald Salami ◽  
Carla Alexandra Sousa ◽  
Maria do Rosário Oliveira Martins ◽  
César Capinha
Keyword(s):  
Machine Learning ◽  
Operating Characteristic ◽  
Predictive Accuracy ◽  
Predictive Performance ◽  
Machine Learning Algorithms ◽  
Transport Network ◽  
Air Transport ◽  
Health Concern ◽  
Centrality Measures ◽  
Network Centrality

ABSTRACTThe geographical spread of dengue is a global public health concern. This is largely mediated by the importation of dengue from endemic to non-endemic areas via the increasing connectivity of the global air transport network. The dynamic nature and intrinsic heterogeneity of the air transport network make it challenging to predict dengue importation.Here, we explore the capabilities of state-of-the-art machine learning algorithms to predict dengue importation. We trained four machine learning classifiers algorithms, using a 6-year historical dengue importation data for 21 countries in Europe and connectivity indices mediating importation and air transport network centrality measures. Predictive performance for the classifiers was evaluated using the area under the receiving operating characteristic curve, sensitivity, and specificity measures. Finally, we applied practical model-agnostic methods, to provide an in-depth explanation of our optimal model’s predictions on a global and local scale.Our best performing model achieved high predictive accuracy, with an area under the receiver operating characteristic score of 0.94 and a maximized sensitivity score of 0.88. The predictor variables identified as most important were the source country’s dengue incidence rate, population size, and volume of air passengers. Network centrality measures, describing the positioning of European countries within the air travel network, were also influential to the predictions.We demonstrated the high predictive performance of a machine learning model in predicting dengue importation and the utility of the model-agnostic methods to offer a comprehensive understanding of the reasons behind the predictions. Similar approaches can be utilized in the development of an operational early warning surveillance system for dengue importation.

A relational perspective on pure project performance

2018 ◽  
Vol 41 (6) ◽  
pp. 753-772 ◽  
Author(s):  
Jimmy H.T. Chan ◽  
Anthony C.K. Ko ◽  
Alan K.M. Au ◽  
Matthew C.H. Yeung
Keyword(s):  
Random Effect ◽  
Poisson Model ◽  
Project Teams ◽  
Centrality Measures ◽  
Network Centrality ◽  
Content Type ◽  
Box Office ◽  
The Social ◽  
Commercial Performance ◽  
Artistic Performance

Purpose The understanding of leaders’ network centrality in social networks has been acknowledged as a major topic that can advance the social network field; most studies in this area have either taken firms as the subject by which the network centrality of firms was measured or/and have been conducted for the functional project context. Very little research has been done in the pure project context. This paper aims to revisit the centrality–performance link in the singular specialized project context. Design/methodology/approach The proposed relationships using panel data on 48 movie directors who lead pure projects has been studied. Freeman’s (1979) and Wasserman and Faust’s (1994) procedures have been adopted to compute our three centrality measures and their effects have been examined on box-office and artistic performance. A random effect and a mixed-effects Poisson model have been fit to examine the significance of the centrality–performance relationship. Findings The findings provide empirical evidence to support three out of the six hypotheses. The findings suggested that degree and closeness centrality are positively related to commercial performance and betweenness centrality is negatively related to commercial performance. However, it was found that only the degree centrality is related to artistic performance. Originality/value This study has two features that distinguish it from prior studies that link centrality to performance. First, the focus is on centrality attached to the leaders instead of the centrality attached to functional project teams or firms, as previously investigated. Second, this study is the first attempt of its kind to analyse the proposed relationship for an Asian market.

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