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- W4250272557 abstract "Analogous to sequence alignment, network alignment (NA) can be used to transfer biological knowledge across species between conserved network regions. NA faces two algorithmic challenges: 1) Which cost function to use to capture similarities between nodes in different networks? 2)Which alignment strategy to use to rapidly identify high-scoring alignments from all possible alignments? We break down existing state-of-the-art methods that use both different cost functions and different alignment strategies to evaluate each combination of their cost functions and alignment strategies. We find that a combination of the cost function of one method and the alignment strategy of another method beats the existing methods. Hence, we propose this combination as a novel superior NA method. Then, since human aging is hard to study experimentally due to long lifespan, we use NA to transfer aging-related knowledge from well annotated model species to poorly annotated human. By doing so, we produce novel human aging-related knowledge, which complements currently available knowledge about aging that has been obtained mainly by sequence alignment. We demonstrate significant similarity between topological and functional properties of our novel predictions and those of known aging-related genes. We are the first to use NA to learn more about aging." @default.
- W4250272557 created "2022-05-12" @default.
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- W4250272557 date "2014-09-20" @default.
- W4250272557 modified "2023-09-23" @default.
- W4250272557 title "Global network alignment in the context of aging" @default.
- W4250272557 cites W1974219242 @default.
- W4250272557 doi "https://doi.org/10.1145/2649387.2660557" @default.
- W4250272557 hasPublicationYear "2014" @default.
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