A knowledge based approach for representing and reasoning about signaling networks

被引：21

作者：

Baral, C. ^{[1
]}

Chancellor, K. ^{[1
]}

Tran, N. ^{[1
]}

Tran, N. L. ^{[2
]}

Joy, A. ^{[2
]}

Berens, M. ^{[2
]}

机构：

[1] Arizona State Univ, Ira A Fulton Sch Engn, Dept Comp Sci & Engn, Tempe, AZ 85281 USA

[2] Translat Genom Res Inst, Phoenix, AZ 85004 USA

来源：

BIOINFORMATICS | 2004年 / 20卷

关键词：

D O I：

10.1093/bioinformatics/bth918

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

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 NF kappa B related signaling pathway to illustrate the kinds of reasoning and representation that our system can currently do.

引用

页码：15 / 22

页数：8

共 31 条

[1] Signalling pathways of the TNF superfamily: A double-edged sword [J].