The paper is dedicated to preliminary results and validation of the distributed solution for causal role attribution in gene network expansion problem. The key ingredients of the solution are the web application based on Shiny framework, RBOINC backend as an interface between R language and BOINC desktop grid framework, and parallel (multicore) implementation of the Peter-Clark (PC) algorithm for causal role attribution. The approach is technically validated on a gene network expansion problem for the grapevine (Vitis vinifera)
Dolgaleva, D.; Pelagalli, C.; Pilati, S.; Blanzieri, E.; Cavecchia, V.; Astafiev, S.; Rumyantsev, A. (2023). Pair of genes: technical validation of distributed causal role attribution to gene network expansion. In: Parallel Computing Technologies 17th International Conference, PaCT 2023, Astana, Kazakhstan, August 21–25, 2023: Springer. (LECTURE NOTES IN COMPUTER SCIENCE): 69-82. ISBN: 9783031416729. doi: 10.1007/978-3-031-41673-6_6 handle: https://hdl.handle.net/10449/81895
Pair of genes: technical validation of distributed causal role attribution to gene network expansion
Pilati, Stefania;
2023-01-01
Abstract
The paper is dedicated to preliminary results and validation of the distributed solution for causal role attribution in gene network expansion problem. The key ingredients of the solution are the web application based on Shiny framework, RBOINC backend as an interface between R language and BOINC desktop grid framework, and parallel (multicore) implementation of the Peter-Clark (PC) algorithm for causal role attribution. The approach is technically validated on a gene network expansion problem for the grapevine (Vitis vinifera)
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