A formal MIM specification and tools for the common exchange of MIM diagrams: an XML-Based format, an API, and a validation method

Luna, Augustin; Karac, Evrim I; Sunshine, Margot; Chang, Lucas; Nussinov, Ruth; Aladjem, Mirit I.; Kohn, Kurt W.

doi:10.1186/1471-2105-12-167

Cited by 20 publications

(16 citation statements)

References 28 publications

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“…Fig. 1 shows a wiring diagram for the current model using the Molecular Interaction Map (MIM) notation for bioregulatory networks and drawn using PathVisio-MIM [ 29 , 30 ]. Each interaction is labelled and described in Table 1 ; these descriptions are used to label the reactions in the SBML model file.…”

Section: Methodsmentioning

confidence: 99%

Predicted Role of NAD Utilization in the Control of Circadian Rhythms during DNA Damage Response

Luna

McFadden²,

Aladjem³

et al. 2015

PLoS Comput Biol

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The circadian clock is a set of regulatory steps that oscillate with a period of approximately 24 hours influencing many biological processes. These oscillations are robust to external stresses, and in the case of genotoxic stress (i.e. DNA damage), the circadian clock responds through phase shifting with primarily phase advancements. The effect of DNA damage on the circadian clock and the mechanism through which this effect operates remains to be thoroughly investigated. Here we build an in silico model to examine damage-induced circadian phase shifts by investigating a possible mechanism linking circadian rhythms to metabolism. The proposed model involves two DNA damage response proteins, SIRT1 and PARP1, that are each consumers of nicotinamide adenine dinucleotide (NAD), a metabolite involved in oxidation-reduction reactions and in ATP synthesis. This model builds on two key findings: 1) that SIRT1 (a protein deacetylase) is involved in both the positive (i.e. transcriptional activation) and negative (i.e. transcriptional repression) arms of the circadian regulation and 2) that PARP1 is a major consumer of NAD during the DNA damage response. In our simulations, we observe that increased PARP1 activity may be able to trigger SIRT1-induced circadian phase advancements by decreasing SIRT1 activity through competition for NAD supplies. We show how this competitive inhibition may operate through protein acetylation in conjunction with phosphorylation, consistent with reported observations. These findings suggest a possible mechanism through which multiple perturbations, each dominant during different points of the circadian cycle, may result in the phase advancement of the circadian clock seen during DNA damage.

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Section: Methodsmentioning

confidence: 99%

Predicted Role of NAD Utilization in the Control of Circadian Rhythms during DNA Damage Response

Luna

McFadden²,

Aladjem³

et al. 2015

PLoS Comput Biol

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“…The MIM helps free readers from a linear view of events and gain a better understanding of control loops involved in these pathways [6]. A machine-readable version of the MIM is provided as Additional file 1 viewable using PathVisio-MIM ( http://discover.nci.nih.gov/mim/mim_pathvisio.html) [7].…”

Section: Introductionmentioning

confidence: 99%

SIRT1/PARP1 crosstalk: connecting DNA damage and metabolism

2013

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An intricate network regulates the activities of SIRT1 and PARP1 proteins and continues to be uncovered. Both SIRT1 and PARP1 share a common co-factor nicotinamide adenine dinucleotide (NAD+) and several common substrates, including regulators of DNA damage response and circadian rhythms. We review this complex network using an interactive Molecular Interaction Map (MIM) to explore the interplay between these two proteins. Here we discuss how NAD + competition and post-transcriptional/translational feedback mechanisms create a regulatory network sensitive to environmental cues, such as genotoxic stress and metabolic states, and examine the role of those interactions in DNA repair and ultimately, cell fate decisions.

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“…Artificial neural networks were used to model gene expression ( Vohradsky 2001 ). Molecular interaction maps are a popular graph-based formalism created by Kohn in 1999 ( Kohn 1999 , Kohn et al 2006 , Luna et al 2011 ) that influenced the SBGN standard ( Le Novère et al 2009 ). Other graph-based formalisms include modular interaction networks ( Yartseva et al 2007 ) and logical interaction hypergraphs ( Klamt et al 2006 ).…”

Section: Modeling Formalismsmentioning

confidence: 99%

Modeling formalisms in Systems Biology

et al. 2011

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Systems Biology has taken advantage of computational tools and high-throughput experimental data to model several biological processes. These include signaling, gene regulatory, and metabolic networks. However, most of these models are specific to each kind of network. Their interconnection demands a whole-cell modeling framework for a complete understanding of cellular systems. We describe the features required by an integrated framework for modeling, analyzing and simulating biological processes, and review several modeling formalisms that have been used in Systems Biology including Boolean networks, Bayesian networks, Petri nets, process algebras, constraint-based models, differential equations, rule-based models, interacting state machines, cellular automata, and agent-based models. We compare the features provided by different formalisms, and discuss recent approaches in the integration of these formalisms, as well as possible directions for the future.

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A formal MIM specification and tools for the common exchange of MIM diagrams: an XML-Based format, an API, and a validation method

Cited by 20 publications

References 28 publications

Predicted Role of NAD Utilization in the Control of Circadian Rhythms during DNA Damage Response

Predicted Role of NAD Utilization in the Control of Circadian Rhythms during DNA Damage Response

SIRT1/PARP1 crosstalk: connecting DNA damage and metabolism

Modeling formalisms in Systems Biology

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