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Open AccessMetabolic network alignment in large scale by network compression
Metabolic network alignment is a system scale comparative analysis that discovers important similarities and differences across different metabolisms and organisms. Although the problem of aligning metabolic n...
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Article
Open AccessHIDEN: Hierarchical decomposition of regulatory networks
Transcription factors regulate numerous cellular processes by controlling the rate of production of each gene. The regulatory relations are modeled using transcriptional regulatory networks. Recent studies hav...
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Open AccessA scalable method for identifying frequent subtrees in sets of large phylogenetic trees
We consider the problem of finding the maximum frequent agreement subtrees (MFASTs) in a collection of phylogenetic trees. Existing methods for this problem often do not scale beyond datasets with around 100 t...
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Article
Open AccessA scalable method for discovering significant subnetworks
Study of biological networks is an essential first step to understand the complex functions they govern in different organisms. The topology of interactions that define how biological networks operate is often...
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Article
Open AccessHierarchical decomposition of dynamically evolving regulatory networks
Gene regulatory networks describe the interplay between genes and their products. These networks control almost every biological activity in the cell through interactions. The hierarchy of genes in these netwo...
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Open AccessIndexing a protein-protein interaction network expedites network alignment
Network query problem aligns a small query network with an arbitrarily large target network. The complexity of this problem grows exponentially with the number of nodes in the query network if confidence in th...
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Open AccessSignal reachability facilitates characterization of probabilistic signaling networks
Studying biological networks is of extreme importance in understanding cellular functions. These networks model interactions between molecules in each cell. A large volume of research has been done to uncover ...
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Article
Open AccessIdentifying the topology of signaling networks from partial RNAi data
Methods for inferring signaling networks using single gene knockdown RNAi experiments and reference networks have been proposed in recent years. These methods assume that RNAi information is available for all ...
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Article
Open AccessIdentification of large disjoint motifs in biological networks
Biological networks provide great potential to understand how cells function. Network motifs, frequent topological patterns, are key structures through which biological networks operate. Finding motifs in biol...
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Open AccessSelected research articles from the 2016 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC)
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Open AccessSelected research articles from the 2017 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC)
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Open AccessCounting motifs in dynamic networks
A network motif is a sub-network that occurs frequently in a given network. Detection of such motifs is important since they uncover functions and local properties of the given biological network. Finding moti...
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Open AccessProMotE: an efficient algorithm for counting independent motifs in uncertain network topologies
Identifying motifs in biological networks is essential in uncovering key functions served by these networks. Finding non-overlap** motif instances is however a computationally challenging task. The fact that...
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Article
Open AccessShortest path counting in probabilistic biological networks
Biological regulatory networks, representing the interactions between genes and their products, control almost every biological activity in the cell. Shortest path search is critical to apprehend the structure...
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Article
Open AccessSelected research articles from the 2018 International Workshop on Computational Network Biology: Modeling, Analysis, and Control (CNB-MAC)
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Article
Open AccessCharacterizing building blocks of resource constrained biological networks
Identification of motifs–recurrent and statistically significant patterns–in biological networks is the key to understand the design principles, and to infer governing mechanisms of biological systems. This, h...