Airway remodeling: Systems biology approach, from bench to bedside.

Technol Health Care. 2016 Jun 10;

Authors: Najafi A, Ghanei M, Jamalkandi SA

Abstract
Airway Remodeling, a patho-physiologic process, is considered as a key feature of chronic airway diseases. In recent years, our understanding of the complex diseases has increased significantly by the use of combined approaches, including systems biology, which may contribute to the development of personalized and predictive medicine approaches. Integrative analysis, along with the cooperation of clinicians, computer scientists, research scientists, and bench scientists, has become an important part of the experimental design and therapeutic strategies in the era of omics. The airway remodeling process is the result of the dysregulation of several signaling pathways that modulate the airway regeneration; therefore, high-throughput experiments and systems biology approach can help to understand this process better. The study reviews related literature and is consistent with the existing clinical evidence.

PMID: 27315153 [PubMed - as supplied by publisher]

Differential RNA-seq, Multi-Network Analysis and Metabolic Regulation Analysis of Kluyveromyces marxianus Reveals a Compartmentalised Response to Xylose.

PLoS One. 2016;11(6):e0156242

Authors: Schabort DT, Letebele PK, Steyn L, Kilian SG, du Preez JC

Abstract
We investigated the transcriptomic response of a new strain of the yeast Kluyveromyces marxianus, in glucose and xylose media using RNA-seq. The data were explored in a number of innovative ways using a variety of networks types, pathway maps, enrichment statistics, reporter metabolites and a flux simulation model, revealing different aspects of the genome-scale response in an integrative systems biology manner. The importance of the subcellular localisation in the transcriptomic response is emphasised here, revealing new insights. As was previously reported by others using a rich medium, we show that peroxisomal fatty acid catabolism was dramatically up-regulated in a defined xylose mineral medium without fatty acids, along with mechanisms to activate fatty acids and transfer products of β-oxidation to the mitochondria. Notably, we observed a strong up-regulation of the 2-methylcitrate pathway, supporting capacity for odd-chain fatty acid catabolism. Next we asked which pathways would respond to the additional requirement for NADPH for xylose utilisation, and rationalised the unexpected results using simulations with Flux Balance Analysis. On a fundamental level, we investigated the contribution of the hierarchical and metabolic regulation levels to the regulation of metabolic fluxes. Metabolic regulation analysis suggested that genetic level regulation plays a major role in regulating metabolic fluxes in adaptation to xylose, even for the high capacity reactions, which is unexpected. In addition, isozyme switching may play an important role in re-routing of metabolic fluxes in subcellular compartments in K. marxianus.

PMID: 27315089 [PubMed - as supplied by publisher]

Heterologous vaccine effects.

Vaccine. 2016 Jun 13;

Authors: Saadatian-Elahi M, Aaby P, Shann F, Netea MG, Levy O, Louis J, Picot V, Greenberg M, Warren W

Abstract
The heterologous or non-specific effects (NSEs) of vaccines, at times defined as "off-target effects" suggest that they can affect the immune response to organisms other than their pathogen-specific intended purpose. These NSEs have been the subject of clinical, immunological and epidemiological studies and are increasingly recognized as an important biological process by a growing group of immunologists and epidemiologists. Much remain to be learned about the extent and underlying mechanisms for these effects. The conference "Off-target effects of vaccination" held in Annecy-France (June 8-10 2015) intended to take a holistic approach drawing from the fields of immunology, systems biology, epidemiology, bioinformatics, public health and regulatory science to address fundamental questions of immunological mechanisms, as well as translational questions about vaccines NSEs. NSE observations were examined using case-studies on live attenuated vaccines and non-live vaccines followed by discussion of studies of possible biological mechanisms. Some possible pathways forward in the study of vaccines NSE were identified and discussed by the expert group.

PMID: 27312214 [PubMed - as supplied by publisher]

A Systems Biology Approach for Identifying Hepatotoxicant Groups Based on Similarity in Mechanisms of Action and Chemical Structure.

Methods Mol Biol. 2016;1425:339-59

Authors: Hebels DG, Rasche A, Herwig R, van Westen GJ, Jennen DG, Kleinjans JC

Abstract
When evaluating compound similarity, addressing multiple sources of information to reach conclusions about common pharmaceutical and/or toxicological mechanisms of action is a crucial strategy. In this chapter, we describe a systems biology approach that incorporates analyses of hepatotoxicant data for 33 compounds from three different sources: a chemical structure similarity analysis based on the 3D Tanimoto coefficient, a chemical structure-based protein target prediction analysis, and a cross-study/cross-platform meta-analysis of in vitro and in vivo human and rat transcriptomics data derived from public resources (i.e., the diXa data warehouse). Hierarchical clustering of the outcome scores of the separate analyses did not result in a satisfactory grouping of compounds considering their known toxic mechanism as described in literature. However, a combined analysis of multiple data types may hypothetically compensate for missing or unreliable information in any of the single data types. We therefore performed an integrated clustering analysis of all three data sets using the R-based tool iClusterPlus. This indeed improved the grouping results. The compound clusters that were formed by means of iClusterPlus represent groups that show similar gene expression while simultaneously integrating a similarity in structure and protein targets, which corresponds much better with the known mechanism of action of these toxicants. Using an integrative systems biology approach may thus overcome the limitations of the separate analyses when grouping liver toxicants sharing a similar mechanism of toxicity.

PMID: 27311473 [PubMed - in process]

Molecular profiles to biology and pathways: a systems biology approach.

Chin J Cancer. 2016;35(1):53

Authors: Van Laere S, Dirix L, Vermeulen P

Abstract
Interpreting molecular profiles in a biological context requires specialized analysis strategies. Initially, lists of relevant genes were screened to identify enriched concepts associated with pathways or specific molecular processes. However, the shortcoming of interpreting gene lists by using predefined sets of genes has resulted in the development of novel methods that heavily rely on network-based concepts. These algorithms have the advantage that they allow a more holistic view of the signaling properties of the condition under study as well as that they are suitable for integrating different data types like gene expression, gene mutation, and even histological parameters.

PMID: 27311441 [PubMed - in process]

Overexpression of Catalase Diminishes Oxidative Cysteine Modifications of Cardiac Proteins.

PLoS One. 2015;10(12):e0144025

Authors: Yao C, Behring JB, Shao D, Sverdlov AL, Whelan SA, Elezaby A, Yin X, Siwik DA, Seta F, Costello CE, Cohen RA, Matsui R, Colucci WS, McComb ME, Bachschmid MM

Abstract
Reactive protein cysteine thiolates are instrumental in redox regulation. Oxidants, such as hydrogen peroxide (H2O2), react with thiolates to form oxidative post-translational modifications, enabling physiological redox signaling. Cardiac disease and aging are associated with oxidative stress which can impair redox signaling by altering essential cysteine thiolates. We previously found that cardiac-specific overexpression of catalase (Cat), an enzyme that detoxifies excess H2O2, protected from oxidative stress and delayed cardiac aging in mice. Using redox proteomics and systems biology, we sought to identify the cysteines that could play a key role in cardiac disease and aging. With a 'Tandem Mass Tag' (TMT) labeling strategy and mass spectrometry, we investigated differential reversible cysteine oxidation in the cardiac proteome of wild type and Cat transgenic (Tg) mice. Reversible cysteine oxidation was measured as thiol occupancy, the ratio of total available versus reversibly oxidized cysteine thiols. Catalase overexpression globally decreased thiol occupancy by ≥1.3 fold in 82 proteins, including numerous mitochondrial and contractile proteins. Systems biology analysis assigned the majority of proteins with differentially modified thiols in Cat Tg mice to pathways of aging and cardiac disease, including cellular stress response, proteostasis, and apoptosis. In addition, Cat Tg mice exhibited diminished protein glutathione adducts and decreased H2O2 production from mitochondrial complex I and II, suggesting improved function of cardiac mitochondria. In conclusion, our data suggest that catalase may alleviate cardiac disease and aging by moderating global protein cysteine thiol oxidation.

PMID: 26642319 [PubMed - indexed for MEDLINE]

Systems biology of IL-6, IL-12 family cytokines.

Cytokine Growth Factor Rev. 2015 Oct;26(5):595-602

Authors: Dittrich A, Hessenkemper W, Schaper F

Abstract
Interleukin-6-type cytokines play important roles in the communication between cells of multicellular organisms. They are involved in the regulation of complex cellular processes such as proliferation and differentiation and act as key player during inflammation and immune response. A major challenge is to understand how these complex non-linear processes are connected and regulated. Systems biology approaches are used to tackle this challenge in an iterative process of quantitative experimental and mathematical analyses. Here we review quantitative experimental studies and systems biology approaches dealing with the function of Interleukin-6-type cytokines in physiological and pathophysiological conditions. These approaches cover the analyses of signal transduction on a cellular level up to pharmacokinetic and pharmacodynamic studies on a whole organism level.

PMID: 26187858 [PubMed - indexed for MEDLINE]

@MInter: Automated Text-mining of Microbial Interactions.

Bioinformatics. 2016 Jun 16;

Authors: Lim KM, Li C, Chng KR, Nagarajan N

Abstract
MOTIVATION: Microbial consortia are frequently defined by numerous interactions within the community that are key to understanding their function. While microbial interactions have been extensively studied experimentally, information regarding them is dispersed in the scientific literature. As manual collation is an infeasible option, automated data processing tools are needed to make this information easily accessible.
RESULTS: We present @MInter, an automated information extraction system based on Support Vector Machines to analyze paper abstracts and infer microbial interactions. @MInter was trained and tested on a manually curated gold standard dataset of 735 species interactions and 3,917 annotated abstracts, constructed as part of this study. Cross-validation analysis showed that @MInter is able to detect abstracts pertaining to one or more microbial interactions with high specificity (specificity = 95%, AUC = 0.97). Despite challenges in identifying specific microbial interactions in an abstract (interaction level recall = 95%, precision = 25%), @MInter was shown to reduce annotator workload 13-fold compared to alternate approaches. Applying @MInter to 175 bacterial species abundant on human skin, we identified a network of 357 literature-reported microbial interactions, demonstrating its utility for the study of microbial communities.
AVAILABILITY: @MInter is freely available at https://github.com/CSB5/atminter CONTACT: nagarajann@gis.a-star.edu.sg SUPPLEMENTARY INFORMATION: Supplementary data is available at Bioinformatics online.

PMID: 27312413 [PubMed - as supplied by publisher]

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Progress and prospects in pharmacogenetics of antidepressant drugs.

Expert Opin Drug Metab Toxicol. 2016 Jun 16;

Authors: Fabbri C, Crisafulli C, Calabrò M, Spina E, Serretti A

Abstract
INTRODUCTION: Depression is responsible for the most part of the personal and socio-economic burden due to psychiatric disorders. Since antidepressant response clusters in families, pharmacogenetics represents a meaningful tool to provide tailored treatments and improve the prognosis of depression.
AREAS COVERED: This review aims to summarize and discuss the pharmacogenetics of antidepressant drugs in major depressive disorder, with a focus on the most replicated genes, genome-wide association studies (GWAS), but also on the findings provided by new and promising analysis methods. In particular, multimarker tests such as pathway analysis and polygenic risk scores increase the power of detecting associations compared to the analysis of individual polymorphisms. Since genetic variants are not necessarily associated with a change in protein level, gene expression studies may provide complementary information to genetic studies. Finally, the pharmacogenetic tests that have been investigated for clinical application are discussed.
EXPERT OPINION: Despite the lack of widespread clinical applications, preliminary results suggest that pharmacogenetics may be useful to guide antidepressant treatment. The US Food and Drug Administration included pharmacogenetic indications in the labeling of several antidepressants. This represented an important official recognition of the clinical relevance of genetic polymorphisms in antidepressant treatment.

PMID: 27310483 [PubMed - as supplied by publisher]

Identification of genetic polymorphisms of CYP2W1 in the three main Chinese ethnicities: Han, Tibetan, and Uighur.

Drug Metab Dispos. 2016 Jun 15;

Authors: Li YW, Kang X, Yang G, Dai PG, Chen C, Wang HJ

Abstract
CYP2W1 is an orphan member of the cytochrome P450 (CYP) superfamily. Recently, CYP2W1 has gained great research interest because of its unknown enzymatic function and tumor-specific expression property. This study aims to investigate the genetic polymorphisms of the CYP2W1 gene in Chinese populations and explore the functions of the detected variants. All the nine exons and exon-intron junction regions of the CYP2W1 gene were sequenced in 150 Chinese subjects, including 50 Han Chinese, 50 Tibetans, and 50 Uighurs. A total of 26 genetic variants were identified in this study, and 19 polymorphisms were detected in each population. Frequency comparison between populations showed that nine variants exhibited significantly different allelic distributions. A total of 12 different haplotypes were inferred from 150 samples by using the genotype data of nine exonic variants found in this study. CYP2W1*1A, *1B, *2, *4, and *6 were detected as the main alleles/haplotypes. Moreover, one, three, and two ethnically specific haplotypes were observed in the Han, Tibetan and Uighur samples, respectively. Then, the effects of four detected missense mutations (Ala181Thr, Gly376Ser, Val432Ile, and Pro488Leu) on the CYP2W1 protein function were predicted using three in-silico tools, namely, PolyPhen-2, SIFT, and MutationTaster. The results showed that Gly376Ser and Pro488Leu may have deleterious effects. In summary, this study showed that the genetic pattern of CYP2W1 is inter-ethnically different among the three Chinese populations, and this finding can extend our understanding of population genetics of CYP2W1 in the Chinese population.

PMID: 27307299 [PubMed - as supplied by publisher]

Drug-Gene Interactions of Antihypertensive Medications and Risk of Incident Cardiovascular Disease: A Pharmacogenomics Study from the CHARGE Consortium.

PLoS One. 2015;10(10):e0140496

Authors: Bis JC, Sitlani C, Irvin R, Avery CL, Smith AV, Sun F, Evans DS, Musani SK, Li X, Trompet S, Krijthe BP, Harris TB, Quibrera PM, Brody JA, Demissie S, Davis BR, Wiggins KL, Tranah GJ, Lange LA, Sotoodehnia N, Stott DJ, Franco OH, Launer LJ, Stürmer T, Taylor KD, Cupples LA, Eckfeldt JH, Smith NL, Liu Y, Wilson JG, Heckbert SR, Buckley BM, Ikram MA, Boerwinkle E, Chen YD, de Craen AJ, Uitterlinden AG, Rotter JI, Ford I, Hofman A, Sattar N, Slagboom PE, Westendorp RG, Gudnason V, Vasan RS, Lumley T, Cummings SR, Taylor HA, Post W, Jukema JW, Stricker BH, Whitsel EA, Psaty BM, Arnett D

Abstract
BACKGROUND: Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals.
METHODS: Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases).
RESULTS: Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10-8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD.

PMID: 26516778 [PubMed - indexed for MEDLINE]

Pharmacogenomic Testing and Warfarin Management.

Oncol Nurs Forum. 2015 Sep;42(5):563-5

Authors: Maluso A

Abstract
Warfarin has been used for the prevention of thrombosis for more than 50 years and is the most frequently prescribed vitamin K antagonist in North America (Gage & Eby, 2003). Its mode of action is to prevent vitamin K from converting to vitamin KH2, thereby inhibiting clotting factors (Johnson & Cavallari, 2015). Warfarin metabolism is affected by variations in the cytochrome P450 2C9 (CYP2C9) and the vitamin K epoxide reductase complex 1 (VKORC1) genotypes. CYP2C9 affects the drug's pharmacokinetics, or metabolism, whereas VKORC1, the target protein of warfarin, affects the drug's pharmacodynamics, or its impact on cell proteins
.

PMID: 26302287 [PubMed - indexed for MEDLINE]

Dihydropyrimidinase and β-ureidopropionase gene variation and severe fluoropyrimidine-related toxicity.

Pharmacogenomics. 2015;16(12):1367-77

Authors: Kummer D, Froehlich TK, Joerger M, Aebi S, Sistonen J, Amstutz U, Largiadèr CR

Abstract
AIMS: To assess the association of DPYS and UPB1 genetic variation, encoding the catabolic enzymes downstream of dihydropyrimidine dehydrogenase, with early-onset toxicity from fluoropyrimidine-based chemotherapy.
PATIENTS & METHODS: The coding and exon-flanking regions of both genes were sequenced in a discovery subset (164 patients). Candidate variants were genotyped in the full cohort of 514 patients.
RESULTS & CONCLUSIONS: Novel rare deleterious variants in DPYS (c.253C > T and c.1217G > A) were detected once each in toxicity cases and may explain the occurrence of severe toxicity in individual patients, and associations of common variants in DPYS (c.1-1T > C: p(adjusted) = 0.003; OR = 2.53; 95% CI: 1.39-4.62, and c.265-58T > C: p(adjusted) = 0.039; OR = 0.61; 95% CI: 0.38-0.97) with 5-fluorouracil toxicity were replicated.

PMID: 26244261 [PubMed - indexed for MEDLINE]

Community-level cohesion without cooperation.

Elife. 2016 Jun 16;5

Authors: Tikhonov M

Abstract
Recent work draws attention to community-community encounters ('coalescence') as likely an important factor shaping natural ecosystems. This work builds on MacArthur's classic model of competitive coexistence to investigate such community-level competition in a minimal theoretical setting. It is shown that the ability of a species to survive a coalescence event is best predicted by a community-level 'fitness' of its native community rather than the intrinsic performance of the species itself. The model presented here allows formalizing a macroscopic perspective whereby a community harboring organisms at varying abundances becomes equivalent to a single organism expressing genes at different levels. While most natural communities do not satisfy the strict criteria of multicellularity developed by multi-level selection theory, the effective cohesion described here is a generic consequence of resource partitioning, requires no cooperative interactions, and can be expected to be widespread in microbial ecosystems.

PMID: 27310530 [PubMed - as supplied by publisher]

Mechanistic Mathematical Modeling Tests Hypotheses of the Neurovascular Coupling in fMRI.

PLoS Comput Biol. 2016 Jun;12(6):e1004971

Authors: Lundengård K, Cedersund G, Sten S, Leong F, Smedberg A, Elinder F, Engström M

Abstract
Functional magnetic resonance imaging (fMRI) measures brain activity by detecting the blood-oxygen-level dependent (BOLD) response to neural activity. The BOLD response depends on the neurovascular coupling, which connects cerebral blood flow, cerebral blood volume, and deoxyhemoglobin level to neuronal activity. The exact mechanisms behind this neurovascular coupling are not yet fully investigated. There are at least three different ways in which these mechanisms are being discussed. Firstly, mathematical models involving the so-called Balloon model describes the relation between oxygen metabolism, cerebral blood volume, and cerebral blood flow. However, the Balloon model does not describe cellular and biochemical mechanisms. Secondly, the metabolic feedback hypothesis, which is based on experimental findings on metabolism associated with brain activation, and thirdly, the neurotransmitter feed-forward hypothesis which describes intracellular pathways leading to vasoactive substance release. Both the metabolic feedback and the neurotransmitter feed-forward hypotheses have been extensively studied, but only experimentally. These two hypotheses have never been implemented as mathematical models. Here we investigate these two hypotheses by mechanistic mathematical modeling using a systems biology approach; these methods have been used in biological research for many years but never been applied to the BOLD response in fMRI. In the current work, model structures describing the metabolic feedback and the neurotransmitter feed-forward hypotheses were applied to measured BOLD responses in the visual cortex of 12 healthy volunteers. Evaluating each hypothesis separately shows that neither hypothesis alone can describe the data in a biologically plausible way. However, by adding metabolism to the neurotransmitter feed-forward model structure, we obtained a new model structure which is able to fit the estimation data and successfully predict new, independent validation data. These results open the door to a new type of fMRI analysis that more accurately reflects the true neuronal activity.

PMID: 27310017 [PubMed - as supplied by publisher]

Mitochondrial dysfunction remodels one-carbon metabolism in human cells.

Elife. 2016;5

Authors: Bao XR, Ong SE, Goldberger O, Peng J, Sharma R, Thompson DA, Vafai SB, Cox AG, Marutani E, Ichinose F, Goessling W, Regev A, Carr SA, Clish CB, Mootha VK

Abstract
Mitochondrial dysfunction is associated with a spectrum of human disorders, ranging from rare, inborn errors of metabolism to common, age-associated diseases such as neurodegeneration. How these lesions give rise to diverse pathology is not well understood, partly because their proximal consequences have not been well-studied in mammalian cells. Here we provide two lines of evidence that mitochondrial respiratory chain dysfunction leads to alterations in one-carbon metabolism pathways. First, using hypothesis-generating metabolic, proteomic, and transcriptional profiling, followed by confirmatory experiments, we report that mitochondrial DNA depletion leads to an ATF4-mediated increase in serine biosynthesis and transsulfuration. Second, we show that lesioning the respiratory chain impairs mitochondrial production of formate from serine, and that in some cells, respiratory chain inhibition leads to growth defects upon serine withdrawal that are rescuable with purine or formate supplementation. Our work underscores the connection between the respiratory chain and one-carbon metabolism with implications for understanding mitochondrial pathogenesis.

PMID: 27307216 [PubMed - in process]

Advanced Multidimensional Separations in Mass Spectrometry: Navigating the Big Data Deluge.

Annu Rev Anal Chem (Palo Alto Calif). 2016 Jun 12;9(1):387-409

Authors: May JC, McLean JA

Abstract
Hybrid analytical instrumentation constructed around mass spectrometry (MS) is becoming the preferred technique for addressing many grand challenges in science and medicine. From the omics sciences to drug discovery and synthetic biology, multidimensional separations based on MS provide the high peak capacity and high measurement throughput necessary to obtain large-scale measurements used to infer systems-level information. In this article, we describe multidimensional MS configurations as technologies that are big data drivers and review some new and emerging strategies for mining information from large-scale datasets. We discuss the information content that can be obtained from individual dimensions, as well as the unique information that can be derived by comparing different levels of data. Finally, we summarize some emerging data visualization strategies that seek to make highly dimensional datasets both accessible and comprehensible.

PMID: 27306312 [PubMed - in process]

Qualitative dynamics semantics for SBGN process description.

BMC Syst Biol. 2016;10(1):42

Authors: Rougny A, Froidevaux C, Calzone L, Paulevé L

Abstract
BACKGROUND: Qualitative dynamics semantics provide a coarse-grain modeling of networks dynamics by abstracting away kinetic parameters. They allow to capture general features of systems dynamics, such as attractors or reachability properties, for which scalable analyses exist. The Systems Biology Graphical Notation Process Description language (SBGN-PD) has become a standard to represent reaction networks. However, no qualitative dynamics semantics taking into account all the main features available in SBGN-PD had been proposed so far.
RESULTS: We propose two qualitative dynamics semantics for SBGN-PD reaction networks, namely the general semantics and the stories semantics, that we formalize using asynchronous automata networks. While the general semantics extends standard Boolean semantics of reaction networks by taking into account all the main features of SBGN-PD, the stories semantics allows to model several molecules of a network by a unique variable. The obtained qualitative models can be checked against dynamical properties and therefore validated with respect to biological knowledge. We apply our framework to reason on the qualitative dynamics of a large network (more than 200 nodes) modeling the regulation of the cell cycle by RB/E2F.
CONCLUSION: The proposed semantics provide a direct formalization of SBGN-PD networks in dynamical qualitative models that can be further analyzed using standard tools for discrete models. The dynamics in stories semantics have a lower dimension than the general one and prune multiple behaviors (which can be considered as spurious) by enforcing the mutual exclusiveness between the activity of different nodes of a same story. Overall, the qualitative semantics for SBGN-PD allow to capture efficiently important dynamical features of reaction network models and can be exploited to further refine them.

PMID: 27306057 [PubMed - in process]