Chia-Ying Cheng

Mining Bridge and Brick Motifs From Complex Biological Networks for Functionally and Statistically Significant Discovery

A major task for postgenomic systems biology researchers is to systematically catalogue molecules and their interactions within living cells. Advancements in complex-network theory are being made toward uncovering organizing principles that govern cell formation and evolution, but we lack understanding of how molecules and their interactions determine how complex systems function. Molecular bridge motifs include isolated motifs that neither interact nor overlap with others, whereas brick motifs act as network foundations that play a central role in defining global topological organization. To emphasize their structural organizing and evolutionary characteristics, we define bridge motifs as consisting of weak links only and brick motifs as consisting of strong links only, then propose a method for performing two tasks simultaneously, which are as follows: 1) detecting global statistical features and local connection structures in biological networks and 2) locating functionally and statistically significant network motifs. To further understand the role of biological networks in system contexts, we examine functional and topological differences between bridge and brick motifs for predicting biological network behaviors and functions. After observing brick motif similarities between E. coli and S. cerevisiae, we note that bridge motifs differentiate C. elegans from Drosophila and sea urchin in three types of networks. Similarities (differences) in bridge and brick motifs imply similar (different) key circuit elements in the three organisms. We suggest that motif-content analyses can provide researchers with global and local data for real biological networks and assist in the search for either isolated or functionally and topologically overlapping motifs when investigating and comparing biological system functions and behaviors.

Bridge and brick network motifs: Identifying significant building blocks from complex biological systems

OBJECTIVE A major focus in computational system biology research is defining organizing principles that govern complex biological network formation and evolution. The task is considered a major challenge because network behavior and function prediction requires the identification of functionally and statistically important motifs. Here we propose an algorithm for performing two tasks simultaneously: (a) detecting global statistical features and local connection structures in biological networks, and (b) locating functionally and statistically significant network motifs. METHODS AND MATERIAL Two gene regulation networks were tested: the bacteria Escherichia coli and the yeast eukaryote Saccharomyces cerevisiae. To understand their structural organizing principles and evolutionary mechanisms, we defined bridge motifs as composed of weak links only or of at least one weak link and multiple strong links, and defined brick motifs as composed of strong links only. RESULTS After examining functional and topological differences between bridge and brick motifs for predicting biological network behaviors and functions, we found that most genetic network motifs belong to the bridge category. This strongly suggests that the weak-tie links that provide unique paths for signal control significantly impact the signal processing function of transcription networks. CONCLUSIONS Bridge and brick motif content analysis can provide researchers with global and local views of individual real networks and help them locate functionally and topologically overlapping or isolated motifs for purposes of investigating biological system functions, behaviors, and similarities.

Influences of Resource Limitations and Transmission Costs on Epidemic Simulations and Critical Thresholds in Scale-Free Networks

Critical thresholds represent one of the most important diffusion indicators of epidemic outbreaks. However, we believe that recent studies have overemphasized ways that the power-law connectivity distribution features of social networks affect epidemic dynamics and critical thresholds. As a result, two important factors have been overlooked: resource limitations and transmission costs associated with social interactions and daily contact. Here we present our results from the simultaneous application of mean-field theory and an agent-based network simulation approach for analyzing the effects of resources and costs on epidemic dynamics and critical thresholds. Our main findings are: (a) a significant critical threshold does exist when resources and costs are taken into consideration, and it has a lower bound whenever contagion events occur in scale-free networks; (b) when transmission costs increase or individual resources decrease, critical contagion thresholds in scale-free networks grow linearly and steady density curves shrink linearly; (c) regardless of whether the resources of individuals obey delta, uniform, or normal distributions, they have the same critical thresholds and epidemic dynamics as long as the average value of usable resources remains the same across different scale-free networks; and (d) the spread of epidemics in scale-free networks remains controllable as long as resources are properly restricted and intervention strategy investments are significantly increased.

Resources, costs and epidemic thresholds in scale-free social networks

Whether or not a critical threshold exists when epidemic diseases are spread in complex networks is a problem attracting attention from researchers in several disciplines. In 2001, Pastor-Satorras and Vespignani used a computational simulations approach to show that epidemic diseases which spread through scale-free social networks do not have positive critical thresholds. In other words, even if a disease has almost no chance of being transmitted from one person to another, it can still spread throughout a scale-free network. However, they ignored two key factors that have a large impact on epidemic dynamics: economic resource limitations and transmission costs. Every infection event entails tangible or intangible costs in terms of time, energy, or money to the carrier, recipient, or both. Here we apply an agent-based modeling and network-oriented computer simulation approach to analyze the influences of resource limitations and transmission costs on epidemic dynamics and critical thresholds in scale-free networks. Our results indicate that when those resources and costs are taken into consideration, the epidemic dynamics of scale-free networks are very similar to those of homogeneous networks, including the presence of significant critical thresholds. It is hoped that our data will help epidemiologists, public health professionals, and computer scientists working with core questions of epidemic diseases, estimates of epidemic dynamics and spreading, and effective public health policies and immunization strategies.

Resource and remembering influences on acquaintance networks

To better reflect actual human interactions in social network models, the authors take a bottom-up, agent-based modeling and network-oriented simulation approach to analyzing acquaintance network evolution based on local interaction rules. Resources and remembering are considered in addition to common friends, meeting by chance, and leaving and arriving. Based on these factors, friendships that have been established and built up can be strengthened, weakened, or broken up. Using computer simulations, Results from a series of experiments indicate that (a) network topology statistics, especially average degree of nodes, are irrelevant to parametric distributions because they rely on average values for initial parameters; and (b) resource, remembering, and initial friendship all raise the average number of friends and lower both degree of clustering and separation. These findings indicate a strong need for a bottom-up, agent-based modeling and network-oriented simulation approach to social network research, one that stresses interactive rules and experimental simulations.

Bridge and Brick Network Motifs

Researchers are increasingly acknowledging the important role of complex networks in numerous scientific contexts. In this paper we define two kinds of motifs - bridge and brick - for exploring and predicting network behaviors and functions and for identifying differences among network structures. Based on an analysis of these motifs in genetic, social, ecological, and engineering networks, we found significant differences in motif functionality and topology. After initially observing similarities between social networks and their genetic, ecological, and engineering counterparts, we eventually noted greater amounts of brick motif in social networks and greater amounts of bridge motif in the other three types. Our conclusion is that bridge and brick motif content analyses can assist researchers in understanding the small-world and clustering properties of network structures and in investigating network functions and behaviors

Evaluating subjective compositions by the cooperation between human and adaptive agents

We describe a music recommender model that uses intermediate agents to evaluate music composition according to their own rules respectively, and make recommendations to user. After user scoring recommended items, agents can adapt their selection rules to fit user tastes, even when user preferences undergo a rapid change. Depending on the number of users, the model can also be applied to such tasks as critiquing large numbers of music, image, or written compositions in a competitive contest with other judges. Several experiments are reported to test the models ability to adapt to rapidly changing conditions yet still make appropriate decisions and recommendations.