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- W2076131444 abstract "Gene networks are important tools in studying gene-gene relationships and gene function. Understanding the relationships within these networks is an important challenge. Ontologies are a critical tool in helping deal with these data. The use of the Gene Ontology, for example, has become routine in methods for validation, discovery, etc. Here we present a novel algorithm that synthesizes an ontology by considering both extant annotation terms and also the connections between genes in gene networks. The process is efficient and produces easily inspectable ontologies. Because the relationships drawn between terms are heavily influenced by data, we call these Data-Driven Ontologies. We apply this algorithm to both discover new relationships between biological processes and as a tool to compare sets of genes across microrarray experiments. Supplemental data and source code are available at: http://www.ddont.org" @default.
- W2076131444 created "2016-06-24" @default.
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- W2076131444 date "2008-11-01" @default.
- W2076131444 modified "2023-09-28" @default.
- W2076131444 title "DATA-DRIVEN ONTOLOGIES" @default.
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- W2076131444 doi "https://doi.org/10.1142/9789812836939_0003" @default.
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