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Fig. 4 | BMC Systems Biology

Fig. 4

From: Parameter estimation of qualitative biological regulatory networks on high performance computing hardware

Fig. 4

a Qualitative Biological Regulatory Network (BRN) of Hexosamine Biosynthetic Pathway (HBP) intersection with PI3K-mTOR-Myc signaling and P53-MDM2 signalling axis. b CTL observations used in [48] to generate dynamic model in the form of stategraph (as shown in Fig. 5b. a HBP intersection is shown with PI3K-mTOR-Myc siganling nd P53-MDM2 signalling axis. The increased flux of HBP is responsible for hyper O-GlcNAcylation which is implicated in several types of cancers. HBP generates UDP-GlcNAC (Urdine diphosphate N-acetylglucosamine) which is consumed by OGT. Hyper O-GlcNAcylation of CMyc triggers PI3K-mTOR-MYC signalling axis which is involved in cross talk with Forkhead box M1 (FoxM1). FoxM1 is further regulated by OGT. The qualitative BRN shows interconnections of important entities. The nodes/circles represent biological entities whereas interactions between two entities are represented with arrows. There are two types of interactions: activations (labelled with pointed green arrows) and inhibitions (labelled with blunt red arrows). The weight of the arrows indicate threshold of interaction. (see Definition 1). b Three CTL observations used in [48] are listed. These CTL observations are used by parallel SMBioNet implementation for estimation of parameters

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