Abstract
Biological pathways describe different processes and relations within a cell and help to understand the human body. Therefore, they can aid in finding the cause of a genetic disease and thus support treatment decisions. However, identifying pathways affected by mutations based on their internal connections is a complex task. Today, most pathway databases offer only a single keyword search to find pathways. Only a small subset of the databases offer a more complex analysis, such as the ConsensusPathDB and hiPathDB, use an approach based on the relationships between genes. In this contribution, I propose a prototype for analyzing pathways based on their internal topology and relations. Over the course of several months, I aggregated the data of multiple pathway databases. Using in-memory database technology, the prototype traverses the underlying graph of these data to find affected pathways based on a set of genes. The possibility to traverse the pathway graph on the fly might help to find new relationships between diseases and pathways.
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Müller, D. (2014). Ad-hoc Analysis of Genetic Pathways. In: Plattner, H., Schapranow, MP. (eds) High-Performance In-Memory Genome Data Analysis. In-Memory Data Management Research. Springer, Cham. https://doi.org/10.1007/978-3-319-03035-7_7
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DOI: https://doi.org/10.1007/978-3-319-03035-7_7
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