Juyong Park - Academia.edu (original) (raw)
Papers by Juyong Park
PloS one, 2015
Online social media such as Twitter are widely used for mining public opinions and sentiments on ... more Online social media such as Twitter are widely used for mining public opinions and sentiments on various issues and topics. The sheer volume of the data generated and the eager adoption by the online-savvy public are helping to raise the profile of online media as a convenient source of news and public opinions on social and political issues as well. Due to the uncontrollable biases in the population who heavily use the media, however, it is often difficult to measure how accurately the online sphere reflects the offline world at large, undermining the usefulness of online media. One way of identifying and overcoming the online-offline discrepancies is to apply a common analytical and modeling framework to comparable data sets from online and offline sources and cross-analyzing the patterns found therein. In this paper we study the political spectra constructed from Twitter and from legislators' voting records as an example to demonstrate the potential limits of online media as ...
Physical review. E, Statistical, nonlinear, and soft matter physics, 2003
It has been argued that the observed anticorrelation between the degrees of adjacent vertices in ... more It has been argued that the observed anticorrelation between the degrees of adjacent vertices in the network representation of the Internet has its origin in the restriction that no two vertices have more than one edge connecting them. Here, we propose a formalism for modeling ensembles of graphs with single edges only and derive values for the exponents and correlation coefficients characterizing them. Our results confirm that the conjectured mechanism does indeed give rise to correlations of the kind seen in the Internet, although only a part of the measured correlation can be accounted for in this way.
Proceedings of the National Academy of Sciences of the United States of America, Jan 13, 2007
Our enhanced ability to map the structure of various complex networks is increasingly accompanied... more Our enhanced ability to map the structure of various complex networks is increasingly accompanied by the possibility of independently identifying the functional characteristics of each node. Although this led to the observation that nodes with similar characteristics have a tendency to link to each other, in general we lack the tools to quantify the interplay between node properties and the structure of the underlying network. Here we show that when nodes in a network belong to two distinct classes, two independent parameters are needed to capture the detailed interplay between the network structure and node properties. We find that the network structure significantly limits the values of these parameters, requiring a phase diagram to uniquely characterize the configurations available to the system. The phase diagram shows a remarkable independence from the network size, a finding that, together with a proposed heuristic algorithm, allows us to determine its shape even for large net...
Physical review. E, Statistical, nonlinear, and soft matter physics, 2004
The p-star model or exponential random graph is among the oldest and best known of network models... more The p-star model or exponential random graph is among the oldest and best known of network models. Here we give an analytic solution for the particular case of the two-star model, which is one of the most fundamental of exponential random graphs. We derive expressions for a number of quantities of interest in the model and show that the degenerate region of the parameter space observed in computer simulations is a spontaneously symmetry-broken phase separated from the normal phase of the model by a conventional continuous phase transition.
Physical review. E, Statistical, nonlinear, and soft matter physics, 2004
We study the family of network models derived by requiring the expected properties of a graph ens... more We study the family of network models derived by requiring the expected properties of a graph ensemble to match a given set of measurements of a real-world network, while maximizing the entropy of the ensemble. Models of this type play the same role in the study of networks as is played by the Boltzmann distribution in classical statistical mechanics; they offer the best prediction of network properties subject to the constraints imposed by a given set of observations. We give exact solutions of models within this class that incorporate arbitrary degree distributions and arbitrary but independent edge probabilities. We also discuss some more complex examples with correlated edges that can be solved approximately or exactly by adapting various familiar methods, including mean-field theory, perturbation theory, and saddle-point expansions.
Euro-American Workshop on Information Optics, 2011
The 3DTV market has already started and more people have been enjoying new visual experience. But... more The 3DTV market has already started and more people have been enjoying new visual experience. But annoyance of wearing 3D glasses is a problem and the autostereoscopic display still has several limitations unsolved. This presentation discusses these limitations and our approaches to overcome them.
2011 10th Euro-American Workshop on Information Optics, 2011
The 3DTV market has already started and more people have been enjoying new visual experience. But... more The 3DTV market has already started and more people have been enjoying new visual experience. But annoyance of wearing 3D glasses is a problem and the autostereoscopic display still has several limitations unsolved. This presentation discusses these limitations and our approaches to overcome them.
SID Symposium Digest of Technical Papers, 2014
Scientific Reports, 2014
Competition between a complex system's constituents and a corresponding reward mechanism based on... more Competition between a complex system's constituents and a corresponding reward mechanism based on it have profound influence on the functioning, stability, and evolution of the system. But determining the dominance hierarchy or ranking among the constituent parts from the strongest to the weakest -essential in determining reward or penalty -is almost always an ambiguous task due to the incomplete nature of competition networks. Here we introduce "Natural Ranking," a desirably unambiguous ranking method applicable to a complete (full) competition network, and formulate an analytical model based on the Bayesian formula inferring the expected mean and error of the natural ranking of nodes from an incomplete network. We investigate its potential and uses in solving issues in ranking by applying to a real-world competition network of economic and social importance.
Scientific Reports, 2012
The extent to which evolutionary changes have impacted the phenotypic relationships among human d... more The extent to which evolutionary changes have impacted the phenotypic relationships among human diseases remains unclear. In this work, we report that phenotypically similar diseases are connected by the evolutionary constraints on human disease genes. Human disease groups can be classified into slowly or rapidly evolving classes, where the diseases in the slowly evolving class are enriched with morphological phenotypes and those in the rapidly evolving class are enriched with physiological phenotypes. Our findings establish a clear evolutionary connection between disease classes and disease phenotypes for the first time. Furthermore, the high comorbidity found between diseases connected by similar evolutionary constraints enables us to improve the predictability of the relative risk of human diseases. We find the evolutionary constraints on disease genes are a new layer of molecular connection in the network-based exploration of human diseases.
Studies in Computational Intelligence, 2014
Studies in Computational Intelligence, 2014
2013 International Symposium on Ubiquitous Virtual Reality, 2013
2014 13th Annual Workshop on Network and Systems Support for Games, 2014
Physical Review E, 2005
We study Strauss's model of a network with clustering and present... more We study Strauss's model of a network with clustering and present an analytic mean-field solution which is exact in the limit of large network size. Previous computer simulations have revealed a degenerate region in the model's parameter space in which triangles of adjacent edges clump together to form unrealistically dense subgraphs, and perturbation calculations have been found to break down in this region at all orders. Our solution shows that this region corresponds to a classic symmetry-broken phase and that the onset of the degeneracy corresponds to a first-order phase transition in the density of the network.
Molecular Systems Biology, 2009
The impact of disease-causing defects is often not limited to the products of a mutated gene but,... more The impact of disease-causing defects is often not limited to the products of a mutated gene but, thanks to interactions between the molecular components, may also affect other cellular functions, resulting in potential comorbidity effects. By combining information on cellular interactions, disease-gene associations, and population-level disease patterns extracted from Medicare data, we find statistically significant correlations between the underlying structure of cellular networks and disease comorbidity patterns in the human population. Our results indicate that such a combination of population-level data and cellular network information could help build novel hypotheses about disease mechanisms.
Molecular Systems Biology, 2011
Proteins targeting the same subcellular localization tend to participate in mutual protein-protei... more Proteins targeting the same subcellular localization tend to participate in mutual protein-protein interactions (PPIs) and are often functionally associated. Here, we investigated the relationship between disease-associated proteins and their subcellular localizations, based on the assumption that protein pairs associated with phenotypically similar diseases are more likely to be connected via subcellular localization. The spatial constraints from subcellular localization significantly strengthened the disease associations of the proteins connected by subcellular localizations. In particular, certain disease types were more prevalent in specific subcellular localizations. We analyzed the enrichment of disease phenotypes within subcellular localizations, and found that there exists a significant correlation between disease classes and subcellular localizations. Furthermore, we found that two diseases displayed high comorbidity when disease-associated proteins were connected via subcellular localization. We newly explained 7584 disease pairs by using the context of protein subcellular localization, which had not been identified using shared genes or PPIs only. Our result establishes a direct correlation between protein subcellular localization and disease association, and helps to understand the mechanism of human disease progression.
Applied Optics, 2008
Color characteristics of an RGBW (red, green, blue, white) electrophoretic display (EPD) prototyp... more Color characteristics of an RGBW (red, green, blue, white) electrophoretic display (EPD) prototype developed by Samsung Electronics are analyzed. EPD shows strong crosstalk between subpixels because of both the fringe field between subpixels and the scattering phenomena at the display surface. An RGB-to-RGBW color-decomposition algorithm optimized to EPD characteristics is developed that compensates for color deterioration due to the fringe field and scattering phenomena. For the four-color-decomposition algorithm, white is added to the primary colors to enhance the reflectance of the vivid colors while minimizing chroma loss. The psychophysical experimental result shows that images rendered with the algorithms developed in this study are preferred more than 90% of the time over those rendered with algorithms from previous studies. This research proves that, in spite of the limited physical property of EPD, the color quality can be improved dramatically through the use of well-designed color-rendering algorithms.
PLoS ONE, 2014
Competition is ubiquitous in many complex biological, social, and technological systems, playing ... more Competition is ubiquitous in many complex biological, social, and technological systems, playing an integral role in the evolutionary dynamics of the systems. It is often useful to determine the dominance hierarchy or the rankings of the components of the system that compete for survival and success based on the outcomes of the competitions between them. Here we propose a ranking method based on the random walk on the network representing the competitors as nodes and competitions as directed edges with asymmetric weights. We use the edge weights and node degrees to define the gradient on each edge that guides the random walker towards the weaker (or the stronger) node, which enables us to interpret the steady-state occupancy as the measure of the node's weakness (or strength) that is free of unwarranted degree-induced bias. We apply our method to two real-world competition networks and explore the issues of ranking stabilization and prediction accuracy, finding that our method outperforms other methods including the baseline win-loss differential method in sparse networks.
PloS one, 2015
Online social media such as Twitter are widely used for mining public opinions and sentiments on ... more Online social media such as Twitter are widely used for mining public opinions and sentiments on various issues and topics. The sheer volume of the data generated and the eager adoption by the online-savvy public are helping to raise the profile of online media as a convenient source of news and public opinions on social and political issues as well. Due to the uncontrollable biases in the population who heavily use the media, however, it is often difficult to measure how accurately the online sphere reflects the offline world at large, undermining the usefulness of online media. One way of identifying and overcoming the online-offline discrepancies is to apply a common analytical and modeling framework to comparable data sets from online and offline sources and cross-analyzing the patterns found therein. In this paper we study the political spectra constructed from Twitter and from legislators' voting records as an example to demonstrate the potential limits of online media as ...
Physical review. E, Statistical, nonlinear, and soft matter physics, 2003
It has been argued that the observed anticorrelation between the degrees of adjacent vertices in ... more It has been argued that the observed anticorrelation between the degrees of adjacent vertices in the network representation of the Internet has its origin in the restriction that no two vertices have more than one edge connecting them. Here, we propose a formalism for modeling ensembles of graphs with single edges only and derive values for the exponents and correlation coefficients characterizing them. Our results confirm that the conjectured mechanism does indeed give rise to correlations of the kind seen in the Internet, although only a part of the measured correlation can be accounted for in this way.
Proceedings of the National Academy of Sciences of the United States of America, Jan 13, 2007
Our enhanced ability to map the structure of various complex networks is increasingly accompanied... more Our enhanced ability to map the structure of various complex networks is increasingly accompanied by the possibility of independently identifying the functional characteristics of each node. Although this led to the observation that nodes with similar characteristics have a tendency to link to each other, in general we lack the tools to quantify the interplay between node properties and the structure of the underlying network. Here we show that when nodes in a network belong to two distinct classes, two independent parameters are needed to capture the detailed interplay between the network structure and node properties. We find that the network structure significantly limits the values of these parameters, requiring a phase diagram to uniquely characterize the configurations available to the system. The phase diagram shows a remarkable independence from the network size, a finding that, together with a proposed heuristic algorithm, allows us to determine its shape even for large net...
Physical review. E, Statistical, nonlinear, and soft matter physics, 2004
The p-star model or exponential random graph is among the oldest and best known of network models... more The p-star model or exponential random graph is among the oldest and best known of network models. Here we give an analytic solution for the particular case of the two-star model, which is one of the most fundamental of exponential random graphs. We derive expressions for a number of quantities of interest in the model and show that the degenerate region of the parameter space observed in computer simulations is a spontaneously symmetry-broken phase separated from the normal phase of the model by a conventional continuous phase transition.
Physical review. E, Statistical, nonlinear, and soft matter physics, 2004
We study the family of network models derived by requiring the expected properties of a graph ens... more We study the family of network models derived by requiring the expected properties of a graph ensemble to match a given set of measurements of a real-world network, while maximizing the entropy of the ensemble. Models of this type play the same role in the study of networks as is played by the Boltzmann distribution in classical statistical mechanics; they offer the best prediction of network properties subject to the constraints imposed by a given set of observations. We give exact solutions of models within this class that incorporate arbitrary degree distributions and arbitrary but independent edge probabilities. We also discuss some more complex examples with correlated edges that can be solved approximately or exactly by adapting various familiar methods, including mean-field theory, perturbation theory, and saddle-point expansions.
Euro-American Workshop on Information Optics, 2011
The 3DTV market has already started and more people have been enjoying new visual experience. But... more The 3DTV market has already started and more people have been enjoying new visual experience. But annoyance of wearing 3D glasses is a problem and the autostereoscopic display still has several limitations unsolved. This presentation discusses these limitations and our approaches to overcome them.
2011 10th Euro-American Workshop on Information Optics, 2011
The 3DTV market has already started and more people have been enjoying new visual experience. But... more The 3DTV market has already started and more people have been enjoying new visual experience. But annoyance of wearing 3D glasses is a problem and the autostereoscopic display still has several limitations unsolved. This presentation discusses these limitations and our approaches to overcome them.
SID Symposium Digest of Technical Papers, 2014
Scientific Reports, 2014
Competition between a complex system's constituents and a corresponding reward mechanism based on... more Competition between a complex system's constituents and a corresponding reward mechanism based on it have profound influence on the functioning, stability, and evolution of the system. But determining the dominance hierarchy or ranking among the constituent parts from the strongest to the weakest -essential in determining reward or penalty -is almost always an ambiguous task due to the incomplete nature of competition networks. Here we introduce "Natural Ranking," a desirably unambiguous ranking method applicable to a complete (full) competition network, and formulate an analytical model based on the Bayesian formula inferring the expected mean and error of the natural ranking of nodes from an incomplete network. We investigate its potential and uses in solving issues in ranking by applying to a real-world competition network of economic and social importance.
Scientific Reports, 2012
The extent to which evolutionary changes have impacted the phenotypic relationships among human d... more The extent to which evolutionary changes have impacted the phenotypic relationships among human diseases remains unclear. In this work, we report that phenotypically similar diseases are connected by the evolutionary constraints on human disease genes. Human disease groups can be classified into slowly or rapidly evolving classes, where the diseases in the slowly evolving class are enriched with morphological phenotypes and those in the rapidly evolving class are enriched with physiological phenotypes. Our findings establish a clear evolutionary connection between disease classes and disease phenotypes for the first time. Furthermore, the high comorbidity found between diseases connected by similar evolutionary constraints enables us to improve the predictability of the relative risk of human diseases. We find the evolutionary constraints on disease genes are a new layer of molecular connection in the network-based exploration of human diseases.
Studies in Computational Intelligence, 2014
Studies in Computational Intelligence, 2014
2013 International Symposium on Ubiquitous Virtual Reality, 2013
2014 13th Annual Workshop on Network and Systems Support for Games, 2014
Physical Review E, 2005
We study Strauss's model of a network with clustering and present... more We study Strauss's model of a network with clustering and present an analytic mean-field solution which is exact in the limit of large network size. Previous computer simulations have revealed a degenerate region in the model's parameter space in which triangles of adjacent edges clump together to form unrealistically dense subgraphs, and perturbation calculations have been found to break down in this region at all orders. Our solution shows that this region corresponds to a classic symmetry-broken phase and that the onset of the degeneracy corresponds to a first-order phase transition in the density of the network.
Molecular Systems Biology, 2009
The impact of disease-causing defects is often not limited to the products of a mutated gene but,... more The impact of disease-causing defects is often not limited to the products of a mutated gene but, thanks to interactions between the molecular components, may also affect other cellular functions, resulting in potential comorbidity effects. By combining information on cellular interactions, disease-gene associations, and population-level disease patterns extracted from Medicare data, we find statistically significant correlations between the underlying structure of cellular networks and disease comorbidity patterns in the human population. Our results indicate that such a combination of population-level data and cellular network information could help build novel hypotheses about disease mechanisms.
Molecular Systems Biology, 2011
Proteins targeting the same subcellular localization tend to participate in mutual protein-protei... more Proteins targeting the same subcellular localization tend to participate in mutual protein-protein interactions (PPIs) and are often functionally associated. Here, we investigated the relationship between disease-associated proteins and their subcellular localizations, based on the assumption that protein pairs associated with phenotypically similar diseases are more likely to be connected via subcellular localization. The spatial constraints from subcellular localization significantly strengthened the disease associations of the proteins connected by subcellular localizations. In particular, certain disease types were more prevalent in specific subcellular localizations. We analyzed the enrichment of disease phenotypes within subcellular localizations, and found that there exists a significant correlation between disease classes and subcellular localizations. Furthermore, we found that two diseases displayed high comorbidity when disease-associated proteins were connected via subcellular localization. We newly explained 7584 disease pairs by using the context of protein subcellular localization, which had not been identified using shared genes or PPIs only. Our result establishes a direct correlation between protein subcellular localization and disease association, and helps to understand the mechanism of human disease progression.
Applied Optics, 2008
Color characteristics of an RGBW (red, green, blue, white) electrophoretic display (EPD) prototyp... more Color characteristics of an RGBW (red, green, blue, white) electrophoretic display (EPD) prototype developed by Samsung Electronics are analyzed. EPD shows strong crosstalk between subpixels because of both the fringe field between subpixels and the scattering phenomena at the display surface. An RGB-to-RGBW color-decomposition algorithm optimized to EPD characteristics is developed that compensates for color deterioration due to the fringe field and scattering phenomena. For the four-color-decomposition algorithm, white is added to the primary colors to enhance the reflectance of the vivid colors while minimizing chroma loss. The psychophysical experimental result shows that images rendered with the algorithms developed in this study are preferred more than 90% of the time over those rendered with algorithms from previous studies. This research proves that, in spite of the limited physical property of EPD, the color quality can be improved dramatically through the use of well-designed color-rendering algorithms.
PLoS ONE, 2014
Competition is ubiquitous in many complex biological, social, and technological systems, playing ... more Competition is ubiquitous in many complex biological, social, and technological systems, playing an integral role in the evolutionary dynamics of the systems. It is often useful to determine the dominance hierarchy or the rankings of the components of the system that compete for survival and success based on the outcomes of the competitions between them. Here we propose a ranking method based on the random walk on the network representing the competitors as nodes and competitions as directed edges with asymmetric weights. We use the edge weights and node degrees to define the gradient on each edge that guides the random walker towards the weaker (or the stronger) node, which enables us to interpret the steady-state occupancy as the measure of the node's weakness (or strength) that is free of unwarranted degree-induced bias. We apply our method to two real-world competition networks and explore the issues of ranking stabilization and prediction accuracy, finding that our method outperforms other methods including the baseline win-loss differential method in sparse networks.