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000117046 005__ 20190331192646.0
000117046 020__ $$a978-1-4244-0788-0
000117046 0247_ $$2doi$$a10.1109/IEMBS.2007.4352560
000117046 02470 $$2ISI$$a000253467001034
000117046 037__ $$aCONF
000117046 245__ $$aModeling of Multiple Valued Gene Regulatory Networks
000117046 269__ $$a2007
000117046 260__ $$c2007
000117046 336__ $$aConference Papers
000117046 520__ $$aIn silico modeling of Gene Regulatory Networks has gained a lot of attention recently as it gives a very powerful tool to experimental biologists to gather the knowledge gained from different biological experiments and understand the dynamics of the overall system. One of the key dynamics that is often interesting is the steady states of the networks which biologically corresponds to the cellular states. In our previous paper, we gave an efficient method called GenYsis to compute these steady states in Boolean representation of Gene Regulatory Network. It has been observed that protein may be expressed at more then two level of expression. This may result in different cellular outcomes. To address this issue, we present here a multiple-level modeling methodology that allows us to be more accurate. In this paper we extend our software GenYsis to model gene regulatory networks where each node in the network may take multiple values.
000117046 700__ $$aGarg, Abhishek
000117046 700__ $$aMendoza, Luis
000117046 700__ $$aXenarios, Ioannis
000117046 700__ $$0240269$$g167918$$aDe Micheli, Giovanni
000117046 7112_ $$dAugust 22-26, 2007$$cLyon, France$$a29th Annual International Conference of the IEEE. EMBS, 2007
000117046 773__ $$t29th Annual International Conference of the IEEE EMBS$$q1398-1404
000117046 8564_ $$uhttps://infoscience.epfl.ch/record/117046/files/Modeling_of_Multiple_Valued_Gene04352560.pdf$$zn/a$$s421386$$yn/a
000117046 909C0 $$xU11140$$0252283$$pLSI1
000117046 909CO $$pIC$$qGLOBAL_SET$$ooai:infoscience.tind.io:117046$$pconf$$pSTI
000117046 917Z8 $$x112915
000117046 937__ $$aEPFL-CONF-117046
000117046 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000117046 980__ $$aCONF