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79
Title: Inference of gene regulation network topology by perturbation analysis
"... Neural Network This paper addresses the problem of identifying the large-scale topology of gene regulation networks from features that can be derived from microarray data sets. Understanding large-scale structures of gene regulation is fundamentally important in biology. Three main classes of networ ..."
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Cited by 1 (0 self)
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yet whether the scale free features are generic to all biological networks due to the limited availability of information on pathways and connectivity. To overcome these limitations and to expand the knowledge of biological network topology, we propose a novel method for network topology inference
RESEARCH ARTICLE Construction and Analyses of Human Large-Scale Tissue Specific Networks
"... Construction and analyses of tissue specific networks is crucial to unveil the function and organizational structure of biological systems. As a direct method to detect protein dynamics, human proteome-wide expression data provide an valuable resource to investigate the tissue specificity of protein ..."
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of interactions to distill tissue specific networks. Through comparing our tissue specific networks with those inferred from gene expression data, we found our networks have larger scales and higher reliability. Furthermore, we investigated the similar extent of multiple tissue specific networks, which proved
Modeling the Evolution of Degree Correlation in Scale-Free Topology Generators
"... In this paper, we examine the asymptotic behavior of degree correlation (i.e., the joint degree distribution of adjacent nodes) in several scale-free topology generators GED [14], PLRG [1], GLP [11], BA [4], AB [2]. We present a unifying analytical framework that allows tractable analysis of degree ..."
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In this paper, we examine the asymptotic behavior of degree correlation (i.e., the joint degree distribution of adjacent nodes) in several scale-free topology generators GED [14], PLRG [1], GLP [11], BA [4], AB [2]. We present a unifying analytical framework that allows tractable analysis of degree
Conservation and Coevolution in the Scale-Free Human Gene Coexpression Network
"... The role of natural selection in biology is well appreciated. Recently, however, a critical role for physical principles of network self-organization in biological systems has been revealed. Here, we employ a systems level view of genomescale sequence and expression data to examine the interplay be ..."
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between these two sources of order, natural selection and physical self-organization, in the evolution of human gene regulation. The topology of a human gene coexpression network, derived from tissue-specific expression profiles, shows scale-free properties that imply evolutionary selforganization via
A topological analysis of the open source software development community
- In HICSS ’05: Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS’05) - Track 7
, 2005
"... The fast growth of OSS has increased the interest in studying the composition of the OSS community and its collaboration mechanisms. Moreover, the success of a project may be related to the underlying social structure of the OSS development community. In this paper, we perform a quantitative analysi ..."
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Cited by 39 (3 self)
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analysis of Open Source Software developers by studying the entire development community at SourceForge [26]. Statistics and social network properties are explored to find collaborations and the effects of different members in the OSS development community. Small world phenomenon and scale free behaviors
The Inferred Cardiogenic Gene Regulatory Network in the Mammalian Heart
"... Cardiac development is a complex, multiscale process encompassing cell fate adoption, differentiation and morphogenesis. To elucidate pathways underlying this process, a recently developed algorithm to reverse engineer gene regulatory networks was applied to time-course microarray data obtained from ..."
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and filtered to generate scale-free, hierarchical networks that are statistically significant and biologically relevant. The networks are validated with known gene interactions and used to predict regulatory pathways important for the developing mammalian heart. Area under the precision-recall curve
1An iterative feature selection method for GRNs inference by exploring topological properties
"... Abstract—An important problem in bioinformatics is the inference of gene regulatory networks (GRN) from temporal expression profiles. In general, the main limitations faced by GRN inference methods is the small number of samples with huge dimensionalities and the noisy nature of the expression measu ..."
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is based on the Sequential Floating Forward Selection (SFFS) algorithm, with the inclusion of a scale-free (Barabási-Albert) topology information in order to guide the search process to improve inference. The proposed algorithm explores the scale-free property by pruning the search space and using a power
Emergent mating topologies in spatially structured genetic algorithms
- In Proceedings of the Genetic and Evolutionary Computation Conference
, 2006
"... The application of network analysis to emergent mating topologies in spatially structured genetic algorithms is presented in this preliminary study as a framework for inferring evolutionary dynamics in recombinant evolutionary search. Emergent mating topologies of populations evolving on regular, sc ..."
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Cited by 6 (2 self)
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The application of network analysis to emergent mating topologies in spatially structured genetic algorithms is presented in this preliminary study as a framework for inferring evolutionary dynamics in recombinant evolutionary search. Emergent mating topologies of populations evolving on regular
Functional Inference of Complex Anatomical Tendinous Networks at a Macroscopic Scale via Sparse Experimentation
"... In systems and computational biology, much effort is devoted to functional identification of systems and networks at the molecular-or cellular scale. However, similarly important networks exist at anatomical scales such as the tendon network of human fingers: the complex array of collagen fibers tha ..."
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that transmits and distributes muscle forces to finger joints. This network is critical to the versatility of the human hand, and its function has been debated since at least the 16 th century. Here, we experimentally infer the structure (both topology and parameter values) of this network through sparse
A Scale-Free Structure Prior for Graphical Models with Applications in Functional Genomics
"... The problem of reconstructing large-scale, gene regulatory networks from gene expression data has garnered considerable attention in bioinformatics over the past decade with the graphical modeling paradigm having emerged as a popular framework for inference. Analysis in a full Bayesian setting is co ..."
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Cited by 3 (1 self)
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network inference, we design a novel Metropolis-Hastings sampler for graphical models that includes a node labeling as a state space variable. In a simulation study, we demonstrate that the scale-free structure prior outperforms the random structure prior at recovering scale-free networks while
Results 1 - 10
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79