Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 15 of 15 for “"network alignment"”.
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Protein-Protein Interaction Network Alignment
… complexes. A protein -protein interaction network is a graph that consists of proteins as vertices and their interactions as edges. Protein-protein interaction network alignment is very important in identifying protein complexes and predicting protein functions. Many algorithms based on …
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Network alignment on big networks
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-04-06 without embargo terms
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Topological Network Alignment Based on Graphlet Degree Signature
<p>A large number of experimental biological network data of different types are becoming available due to advanced experimental techniques. Network alignment is considered to be one of the most common methods to analyze and compare biological networks to understand evolution, biological …
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Position-aware regularized optimal transport for network alignment
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01
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Incorporating diverse data to improve genetic network alignment with IsoRank
… have the same function (orthologs), I extend the network-alignment algorithm IsoRank to simultaneously align multiple unrelated networks over the same set of nodes. In addition to the original protein-interaction networks, I align genetic-interaction networks, gene-expression correlations, and …
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Large, noisy, and incomplete : mathematics for modern biology
… thesis discusses two problems in this field, network reconstruction and multiple network alignment, and draws the beginnings of a connection between information theory and population genetics. The first section addresses cellular signaling network inference. A central challenge in systems …
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Graph matching by graph neural network
Graph matching or network alignment refers to the problem of matching two correlated graphs. This thesis presents a deep Q learning based method, which represents the matching process by a graph neural network. By breaking the symmetry, the parameterized graph neural network is able to capture a …
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Machine Learning Approaches for Identifying microRNA Targets and Conserved Protein Complexes
… functions. We developed novel strategy for local network alignment, DONA. DONA maps proteins into their domains and uses DDIs to improve the network alignment. We developed novel strategy for constructing an alignment graph and then uses this graph to discover the conserved sub-networks. DONA …
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Mine the node association: Dig into the essence of graphs
… example, competing sampling strategies exist in network embedding based algorithms (e.g., the distant positive sampling strategy, and close negative sampling strategy). Third (the graph challenge), almost any real graph keeps evolving. How to capture the evolution pattern of node association and …
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On the structure and evolution of protein interaction networks
The study of protein interactions from the networks point of view has yielded new insights into systems biology [Bar03, MA03, RSM+02, WS98]. In particular, "network motifs" become apparent as a useful and systematic tool for describing and exploring networks [BP06, MKFV06, MSOI+02, SOMMA02, SV06]. …
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Learning and Control of Network Phenomena
The intersection of dynamical systems and networks are used to model a huge variety of phenomena. From social networks, to traffic routes and self-driving cars, to swarms of robots and multiagent systems, to individuals moving about in a geographical area, networks can represent an enormous variety …
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Matrix estimation with latent permutations
… by various applications such as seriation, network alignment and ranking from pairwise comparisons, we study the problem of estimating a structured matrix with rows and columns shuffled by latent permutations, given noisy and incomplete observations of its entries. This problem is at the …
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Algorithms for the analysis of protein interaction networks
… this data is the protein interaction network: each node of the network represents a protein and an edge between two nodes represents a physical interaction between the two corresponding proteins. This abstraction has proven to be a powerful tool for understanding the systems aspects of …
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Matching in networks: fundamental limits and efficient algorithms
… E-commerce, which generate massive amounts of network data. For example, a friend link on Facebook represents a connection between users, and a rating on Amazon is a connection between a customer and a product. These network data contain extensive information on customers' behaviors and …
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On the analysis of complex networks : fundamental limits, scalable algorithms, and applications
Network models provide a unifying framework for understanding dependencies among variables in data-driven and engineering sciences. Networks can be used to reveal underlying data structures, infer functional modules, and facilitate experiment design. In practice, however, size, uncertainty and …