Planning for Gene Regulatory Network Intervention
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 1834-1838.
Abstract
Modeling the dynamics of cellular processes has recently become a important research area of many disciplines. One of the most important reasons to model a cellular process is to enable high-throughput in-silico experiments that attempt to predict or intervene in the process. These experiments can help accelerate the design of therapies through their cheap replication and alteration. While some techniques exist for reasoning with cellular processes, few take advantage of the flexible and scalable algorithms popularized in AI research. In this domain, where scalability is crucial for feasible application, we apply AI planning based search techniques and demonstrate their advantage over existing enumerative methods.
@inproceedings{ijcai2007p296,
title = {Planning for Gene Regulatory Network Intervention},
author = {Bryce, Daniel and Kim, Seungchan},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {1834--1838},
year = {2007},
url = {https://ijcai.org/proceedings/2007/296},
}
TY - CPAPER TI - Planning for Gene Regulatory Network Intervention AU - Bryce, Daniel AU - Kim, Seungchan T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 1834 EP - 1838 UR - https://ijcai.org/proceedings/2007/296 ER -Copied
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