A knowledge based approach for representing and reasoning about signaling networks

A knowledge based approach for representing and reasoning about signaling networks
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用于表示和推理信令网络的基于知识的方法

DOI:
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发表时间:
2004
期刊:
ISMB/ECCB
影响因子:
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通讯作者:
M. Berens
M. Berens
中科院分区:
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文献类型:
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作者:
Chitta Baral;K. Chancellor;Tran Hoai Nam;Nhan Tran;A. Joy;M. Berens

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动机 在本文中,我们建议使用知识表示语言和推理方法的最新发展,表示和推理的信令网络。我们的方法是不同于大多数其他定性系统生物学方法,因为它是基于推理(或推断),而不是模拟。我们的方法的一些优点是,我们可以使用不完整和部分信息推理的最新进展来处理信号网络知识的差距;并且可以执行各种推理,如规划,假设推理和解释观察。 结果 使用我们的方法,我们已经开发了系统BioSigNet-RR信号网络的表示和推理。我们使用NF κ B相关的信号通路来说明我们的系统目前可以进行的推理和表示。 可用性 该系统可在网站http://www.public.asu.edu/~cbaral/biosignet上获得
MOTIVATION In this paper we propose to use recent developments in knowledge representation languages and reasoning methodologies for representing and reasoning about signaling networks. Our approach is different from most other qualitative systems biology approaches in that it is based on reasoning (or inferencing) rather than simulation. Some of the advantages of our approach are, we can use recent advances in reasoning with incomplete and partial information to deal with gaps in signal network knowledge; and can perform various kinds of reasoning such as planning, hypothetical reasoning and explaining observations. RESULTS Using our approach we have developed the system BioSigNet-RR for representation and reasoning about signaling networks. We use a NFkappaB related signaling pathway to illustrate the kinds of reasoning and representation that our system can currently do. AVAILABILITY The system is available on the Web at http://www.public.asu.edu/~cbaral/biosignet