Browsing by Author "Wolkenhauer, Olaf"
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- ItemAge-dependent effects of UCP2 deficiency on experimental acute pancreatitis in mice(PLoS, 2014-04-10) Muller, Sarah; Kaiser, Hannah; Kruger, Burkhard; Fitzner, Brit; Lange, Falko; Bock, Cristin N.; Nizze, Horst; Ibrahim, Saleh M.; Fuellen, Georg; Wolkenhauer, Olaf; Jaster, RobertReactive oxygen species (ROS) have been implicated in the pathogenesis of acute pancreatitis (AP) for many years but experimental evidence is still limited. Uncoupling protein 2 (UCP2)-deficient mice are an accepted model of age-related oxidative stress. Here, we have analysed how UCP2 deficiency affects the severity of experimental AP in young and older mice (3 and 12 months old, respectively) triggered by up to 7 injections of the secretagogue cerulein (50 μg/kg body weight) at hourly intervals. Disease severity was assessed at time points from 3 hours to 7 days based on pancreatic histopathology, serum levels of alpha-amylase, intrapancreatic trypsin activation and levels of myeloperoxidase (MPO) in lung and pancreatic tissue. Furthermore, in vitro studies with pancreatic acini were performed. At an age of 3 months, UCP2-/- mice and wild-type (WT) C57BL/6 mice were virtually indistinguishable with respect to disease severity. In contrast, 12 months old UCP2-/- mice developed a more severe pancreatic damage than WT mice at late time points after the induction of AP (24 h and 7 days, respectively), suggesting retarded regeneration. Furthermore, a higher peak level of alpha-amylase activity and gradually increased MPO levels in pancreatic and lung tissue were observed in UCP2-/- mice. Interestingly, intrapancreatic trypsin activities (in vivo studies) and intraacinar trypsin and elastase activation in response to cerulein treatment (in vitro studies) were not enhanced but even diminished in the knockout strain. Finally, UCP2-/- mice displayed a diminished ratio of reduced and oxidized glutathione in serum but no increased ROS levels in pancreatic acini. Together, our data indicate an aggravating effect of UCP2 deficiency on the severity of experimental AP in older but not in young mice. We suggest that increased severity of AP in 12 months old UCP2-/- is caused by an imbalanced inflammatory response but is unrelated to acinar cell functions.
- ItemAnnotation-based feature extraction from sets of SBML models(BioMed Central, 2015-04-15) Alm, Rebekka; Waltemath, Dagmar; Wolfien, Markus; Wolkenhauer, Olaf; Henkel, RonBackground: Model repositories such as BioModels Database provide computational models of biological systems for the scientific community. These models contain rich semantic annotations that link model entities to concepts in well-established bio-ontologies such as Gene Ontology. Consequently, thematically similar models are likely to share similar annotations. Based on this assumption, we argue that semantic annotations are a suitable tool to characterize sets of models. These characteristics improve model classification, allow to identify additional features for model retrieval tasks, and enable the comparison of sets of models. Results: In this paper we discuss four methods for annotation-based feature extraction from model sets. We tested all methods on sets of models in SBML format which were composed from BioModels Database. To characterize each of these sets, we analyzed and extracted concepts from three frequently used ontologies, namely Gene Ontology, ChEBI and SBO. We find that three out of the methods are suitable to determine characteristic features for arbitrary sets of models: The selected features vary depending on the underlying model set, and they are also specific to the chosen model set. We show that the identified features map on concepts that are higher up in the hierarchy of the ontologies than the concepts used for model annotations. Our analysis also reveals that the information content of concepts in ontologies and their usage for model annotation do not correlate. Conclusions: Annotation-based feature extraction enables the comparison of model sets, as opposed to existing methods for model-to-keyword comparison, or model-to-model comparison.
- ItemAnti-inflammatory effects of reactive oxygen species : a multi-valued logical model validated by formal concept analysis(BioMed Central, 2014-09) Wollbold, Johannes; Jaster, Robert; Muller, Sarah; Rateitschak, Katja; Wolkenhauer, OlafBackground: Recent findings suggest that in pancreatic acinar cells stimulated with bile acid, a pro-apoptotic effect of reactive oxygen species (ROS) dominates their effect on necrosis and spreading of inflammation. The first effect presumably occurs via cytochrome C release from the inner mitochondrial membrane. A pro-necrotic effect – similar to the one of Ca2+ – can be strong opening of mitochondrial pores leading to breakdown of the membrane potential, ATP depletion, sustained Ca2+ increase and premature activation of digestive enzymes. To explain published data and to understand ROS effects during the onset of acute pancreatitis, a model using multi-valued logic is constructed. Formal concept analysis (FCA) is used to validate the model against data as well as to analyze and visualize rules that capture the dynamics. Results: Simulations for two different levels of bile stimulation and for inhibition or addition of antioxidants reproduce the qualitative behaviour shown in the experiments. Based on reported differences of ROS production and of ROS induced pore opening, the model predicts a more uniform apoptosis/necrosis ratio for higher and lower bile stimulation in liver cells than in pancreatic acinar cells. FCA confirms that essential dynamical features of the data are captured by the model. For instance, high necrosis always occurs together with at least a medium level of apoptosis. At the same time, FCA helps to reveal subtle differences between data and simulations. The FCA visualization underlines the protective role of ROS against necrosis. Conclusions: The analysis of the model demonstrates how ROS and decreased antioxidant levels contribute to apoptosis. Studying the induction of necrosis via a sustained Ca2+ increase, we implemented the commonly accepted hypothesis of ATP depletion after strong bile stimulation. Using an alternative model, we demonstrate that this process is not necessary to generate the dynamics of the measured variables. Opening of plasma membrane channels could also lead to a prolonged increase of Ca2+ and to necrosis. Finally, the analysis of the model suggests a direct experimental testing for the model-based hypothesis of a self-enhancing cycle of cytochrome C release and ROS production by interruption of the mitochondrial electron transport chain.
- ItemCOMODI : an ontology to characterise differences in versions of computational models in biology(BioMed Central, 2016-07-11) Scharm, Martin; Waltemath, Dagmar; Mendes, Pedro; Wolkenhauer, OlafBackground: Open model repositories provide ready-to-reuse computational models of biological systems. Models within those repositories evolve over time, leading to different model versions. Taken together, the underlying changes reflect a model’s provenance and thus can give valuable insights into the studied biology. Currently, however, changes cannot be semantically interpreted. To improve this situation, we developed an ontology of terms describing changes in models. The ontology can be used by scientists and within software to characterise model updates at the level of single changes. When studying or reusing a model, these annotations help with determining the relevance of a change in a given context. Methods: We manually studied changes in selected models from BioModels and the Physiome Model Repository. Using the BiVeS tool for difference detection, we then performed an automatic analysis of changes in all models published in these repositories. The resulting set of concepts led us to define candidate terms for the ontology. In a final step, we aggregated and classified these terms and built the first version of the ontology. Results: We present COMODI, an ontology needed because COmputational MOdels DIffer. It empowers users and software to describe changes in a model on the semantic level. COMODI also enables software to implement user-specific filter options for the display of model changes. Finally, COMODI is a step towards predicting how a change in a model influences the simulation results. Conclusion: COMODI, coupled with our algorithm for difference detection, ensures the transparency of a model’s evolution, and it enhances the traceability of updates and error corrections. COMODI is encoded in OWL. It is openly available at http://comodi.sems.uni-rostock.de/.
- ItemCOVID-19 Disease map, building a computational repository of SARS-CoV-2 virus-host interaction mechanisms(Springer Nature, 2020) Ostaszewski, Marek; Mazein, Alexander; Gillespie, Marc E.; Kuperstein, Inna; Niarakis, Anna; Hermjakob, Henning; Pico, Alexander R.; Willighagen, Egon L.; Evelo, Chris T.; Hasenauer, Jan; Schreiber, Falk; Drager, Andreas; Demir, Emek; Wolkenhauer, Olaf; Furlong, Laura I.; Barillot, Emmanuel; Dopazo, Joaquin; Orta-Resendiz, Aurelio; Messina, Francesco; Valencia, Alfonso; Funahashi, Akira; Kitano, Hiroaki; Auffray, Charles; Balling, Rudi; Schneider, ReinhardWe announce the COVID-19 Disease Map (https://doi.org/10.17881/covid19-disease-map), an effort to build a comprehensive, standardized knowledge repository of SARS-CoV-2 virus-host interaction mechanisms, guided by input from domain experts and based on published work. This knowledge, available in the vast body of existing literature1,2 and the fast-growing number of new SARS-CoV-2 publications, needs rigorous and efficient organization in both human and machine-readable formats.
- ItemDissecting long-term glucose metabolism identifies new susceptibility period for metabolic dysfunction in aged mice(Public Library of Science, 2015) Chauhan, Anuradha; Weiss, Heike; Koch, Franziska; Ibrahim, Saleh M.; Vera, Julio; Wolkenhauer, Olaf; Tiedge, MarkusMetabolic disorders, like diabetes and obesity, are pathogenic outcomes of imbalance in glucose metabolism. Nutrient excess and mitochondrial imbalance are implicated in dysfunctional glucose metabolism with age. We used conplastic mouse strains with defined mitochondrial DNA (mtDNA) mutations on a common nuclear genomic background, and administered a high-fat diet up to 18 months of age. The conplastic mouse strain B6-mtFVB, with a mutation in the mt-Atp8 gene, conferred β-cell dysfunction and impaired glucose tolerance after high-fat diet. To our surprise, despite of this functional deficit, blood glucose levels adapted to perturbations with age. Blood glucose levels were particularly sensitive to perturbations at the early age of 3 to 6 months. Overall the dynamics consisted of a peak between 3–6 months followed by adaptation by 12 months of age. With the help of mathematical modeling we delineate how body weight, insulin and leptin regulate this non-linear blood glucose dynamics. The model predicted a second rise in glucose between 15 and 21 months, which could be experimentally confirmed as a secondary peak. We therefore hypothesize that these two peaks correspond to two sensitive periods of life, where perturbations to the basal metabolism can mark the system for vulnerability to pathologies at later age. Further mathematical modeling may perspectively allow the design of targeted periods for therapeutic interventions and could predict effects on weight loss and insulin levels under conditions of pre-diabetic obesity.
- ItemEnabling multiscale modeling in systems medicine(BioMed Central, 2014-03) Wolkenhauer, Olaf; Auffray, Charles; Brass, Olivier; Clairambault, Jean; Deutsch, Andreas; Drasdo, Dirk; Gervasio, Francesco; Preziosi, Luigi; Maini, Philip; Marciniak-Czochra, Anna; Kossow, Christina; Kuepfer, Lars; Rateitschak, Katja; Ramis-Conde, Ignacio; Ribba, Benjamin; Schuppert, Andreas; Smallwood, Rod; Stamatakos, Georgios; Winter, Felix; Byrne, Helen[See article for abstract].
- ItemEvolution of computational models in BioModels Database and the Physiome Model Repository(BioMed Central, 2018-04-12) Scharm, Martin; Gebhardt, Tom; Toure, Vasundra; Bagnacani, Andrea; Salehzadeh-Yazdi, Ali; Wolkenhauer, Olaf; Waltemath, DagmarENGLISH SUMMARY : Background: A useful model is one that is being (re)used. The development of a successful model does not finish with its publication. During reuse, models are being modified, i.e. expanded, corrected, and refined. Even small changes in the encoding of a model can, however, significantly affect its interpretation. Our motivation for the present study is to identify changes in models and make them transparent and traceable. Methods: We analysed 13734 models from BioModels Database and the Physiome Model Repository. For each model, we studied the frequencies and types of updates between its first and latest release. To demonstrate the impact of changes, we explored the history of a Repressilator model in BioModels Database. Results: We observed continuous updates in the majority of models. Surprisingly, even the early models are still being modified. We furthermore detected that many updates target annotations, which improves the information one can gain from models. To support the analysis of changes in model repositories we developed MoSt, an online tool for visualisations of changes in models. The scripts used to generate the data and figures for this study are available from GitHub github.com/binfalse/BiVeS-StatsGenerator and as a Docker image at hub.docker.com/r/binfalse/bives-statsgenerator. The website most.bio.informatik.uni-rostock.de provides interactive access to model versions and their evolutionary statistics. Conclusion: The reuse of models is still impeded by a lack of trust and documentation. A detailed and transparent documentation of all aspects of the model, including its provenance, will improve this situation. Knowledge about a model’s provenance can avoid the repetition of mistakes that others already faced. More insights are gained into how the system evolves from initial findings to a profound understanding. We argue that it is the responsibility of the maintainers of model repositories to offer transparent model provenance to their users.
- ItemHarmonizing semantic annotations for computational models in biology(Oxford University Press, 2019) Neal, Maxwell Lewis; Konig, Matthias; Nickerson, David; Mısırlı, Goksel; Kalbasi, Reza; Drager, Andreas; Atalag, Koray; Chelliah, Vijayalakshmi; Cooling, Michael T.; Cook, Daniel L.; Crook, Sharon; De Alba, Miguel; Friedman, Samuel H.; Garny, Alan; Gennari, John H.; Gleeson, Padraig; Golebiewski, Martin; Hucka, Michael; Juty, Nick; Myers, Chris; Olivier, Brett G.; Sauro, Herbert M.; Scharm, Martin; Snoep, Jacky L.; Toure, Vasundra; Wipat, Anil; Wolkenhauer, Olaf; Waltemath, DagmarLife science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol.Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the COmputational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation.
- ItemAn integrative network-driven pipeline for systematic identification of lncRNA-associated regulatory network motifs in metastatic melanoma(BMC (part of Springer Nature), 2020-07-23) Singh, Nivedita; Eberhardt, Martin; Wolkenhauer, Olaf; Vera, Julio; Gupta, Shailendra K.Background: Melanoma phenotype and the dynamics underlying its progression are determined by a complex interplay between different types of regulatory molecules. In particular, transcription factors (TFs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) interact in layers that coalesce into large molecular interaction networks. Our goal here is to study molecules associated with the cross-talk between various network layers, and their impact on tumor progression. Results: To elucidate their contribution to disease, we developed an integrative computational pipeline to construct and analyze a melanoma network focusing on lncRNAs, their miRNA and protein targets, miRNA target genes, and TFs regulating miRNAs. In the network, we identified three-node regulatory loops each composed of lncRNA, miRNA, and TF. To prioritize these motifs for their role in melanoma progression, we integrated patient-derived RNAseq dataset from TCGA (SKCM) melanoma cohort, using a weighted multi-objective function. We investigated the expression profile of the top-ranked motifs and used them to classify patients into metastatic and non-metastatic phenotypes. Conclusions: The results of this study showed that network motif UCA1/AKT1/hsamiR- 125b-1 has the highest prediction accuracy (ACC = 0.88) for discriminating metastatic and non-metastatic melanoma phenotypes. The observation is also confirmed by the progression-free survival analysis where the patient group characterized by the metastatic-type expression profile of the motif suffers a significant reduction in survival. The finding suggests a prognostic value of network motifs for the classification and treatment of melanoma.
- ItemMinimum information about a simulation experiment (MIASE)(PLOS, 2011-04) Waltemath, Dagmar; Adams, Richard; Beard, Daniel A.; Bergmann, Frank T.; Balla, Upinder S.; Britten, Randall; Chelliah, Vijayalakshmi; Cooling, Michael T.; Cooper, Jonathan; Crampin, Edmund J.; Garny, Alan; Hoops, Stefan; Hucka, Michael; Hunter, Peter; Klipp, Edda; Laibe, Camille; Miller, Andrew K.; Moraru, Ion; Nickerson, David; Nielsen, Poul; Nikolski, Macha; Sahle, Sven; Sauro, Herbert M.; Schmidt, Henning; Snoep, Jacky L.; Tolle, Dominic; Wolkenhauer, Olaf; Le Novere, NicolasReproducibility of experiments is a basic requirement for science. Minimum Information (MI) guidelines have proved a helpful means of enabling reuse of existing work in modern biology. The Minimum Information Required in the Annotation of Models (MIRIAM) guidelines promote the exchange and reuse of biochemical computational models. However, information about a model alone is not sufficient to enable its efficient reuse in a computational setting. Advanced numerical algorithms and complex modeling workflows used in modern computational biology make reproduction of simulations difficult. It is therefore essential to define the core information necessary to perform simulations of those models. The Minimum Information About a Simulation Experiment describes the minimal set of information that must be provided to make the description of a simulation experiment available to others. It includes the list of models to use and their modifications, all the simulation procedures to apply and in which order, the processing of the raw numerical results, and the description of the final output. MIASE allows for the reproduction of any simulation experiment. The provision of this information, along with a set of required models, guarantees that the simulation experiment represents the intention of the original authors. Following MIASE guidelines will thus improve the quality of scientific reporting, and will also allow collaborative, more distributed efforts in computational modeling and simulation of biological processes.
- ItemParameter identifiability and sensitivity analysis predict targets for enhancement of STAT1 activity in pancreatic cancer and stellate cells(Public Library of Science, 2012-12) Rateitschak, Katja; Winter, Felix; Lange, Falko; Jaster, Robert; Wolkenhauer, OlafThe present work exemplifies how parameter identifiability analysis can be used to gain insights into differences in experimental systems and how uncertainty in parameter estimates can be handled. The case study, presented here, investigates interferon-gamma (IFNc) induced STAT1 signalling in two cell types that play a key role in pancreatic cancer development: pancreatic stellate and cancer cells. IFNc inhibits the growth for both types of cells and may be prototypic of agents that simultaneously hit cancer and stroma cells. We combined time-course experiments with mathematical modelling to focus on the common situation in which variations between profiles of experimental time series, from different cell types, are observed. To understand how biochemical reactions are causing the observed variations, we performed a parameter identifiability analysis. We successfully identified reactions that differ in pancreatic stellate cells and cancer cells, by comparing confidence intervals of parameter value estimates and the variability of model trajectories. Our analysis shows that useful information can also be obtained from nonidentifiable parameters. For the prediction of potential therapeutic targets we studied the consequences of uncertainty in the values of identifiable and nonidentifiable parameters. Interestingly, the sensitivity of model variables is robust against parameter variations and against differences between IFNc induced STAT1 signalling in pancreatic stellate and cancer cells. This provides the basis for a prediction of therapeutic targets that are valid for both cell types.
- ItemThe role of theory and modeling in medical research(Frontiers Media, 2013-12-19) Wolkenhauer, OlafNo abstract available.
- ItemSystems approach to the study of brain damage in the very preterm newborn(Frontiers Media, 2016) Leviton, Alan; Gressens, Pierre; Wolkenhauer, Olaf; Dammann, OlafBackground: A systems approach to the study of brain damage in very preterm newborns has been lacking. Methods: In this perspective piece, we offer encephalopathy of prematurity as an example of the complexity and interrelatedness of brain-damaging molecular processes that can be initiated inflammatory phenomena. Results: Using three transcription factors, nuclear factor-kappa B (NF-κB), Notch-1, and nuclear factor erythroid 2 related factor 2 (NRF2), we show the inter-connectedness of signaling pathways activated by some antecedents of encephalopathy of prematurity. Conclusions: We hope that as biomarkers of exposures and processes leading to brain damage in the most immature newborns become more readily available, those who apply a systems approach to the study of neuroscience can be persuaded to study the pathogenesis of brain disorders in the very preterm newborn.
- ItemTRAPLINE : a standardized and automated pipeline for RNA sequencing data analysis, evaluation and annotation(BioMed Central, 2016) Wolfien, Markus; Rimmbach, Christian; Schmitz, Ulf; Jung, Julia Jeannine; Krebs, Stefan; Steinhoff, Gustav; David, Robert; Wolkenhauer, OlafBackground: Technical advances in Next Generation Sequencing (NGS) provide a means to acquire deeper insights into cellular functions. The lack of standardized and automated methodologies poses a challenge for the analysis and interpretation of RNA sequencing data. We critically compare and evaluate state-of-the-art bioinformatics approaches and present a workflow that integrates the best performing data analysis, data evaluation and annotation methods in a Transparent, Reproducible and Automated PipeLINE (TRAPLINE) for RNA sequencing data processing (suitable for Illumina, SOLiD and Solexa). Results: Comparative transcriptomics analyses with TRAPLINE result in a set of differentially expressed genes, their corresponding protein-protein interactions, splice variants, promoter activity, predicted miRNA-target interactions and files for single nucleotide polymorphism (SNP) calling. The obtained results are combined into a single file for downstream analysis such as network construction. We demonstrate the value of the proposed pipeline by characterizing the transcriptome of our recently described stem cell derived antibiotic selected cardiac bodies ('aCaBs'). Conclusion: TRAPLINE supports NGS-based research by providing a workflow that requires no bioinformatics skills, decreases the processing time of the analysis and works in the cloud. The pipeline is implemented in the biomedical research platform Galaxy and is freely accessible via www.sbi.uni-rostock.de/RNAseqTRAPLINE or the specific Galaxy manual page (https://usegalaxy.org/u/mwolfien/p/trapline---manual).
- ItemWhy model?(Frontiers Media, 2014-01-28) Wolkenhauer, OlafNext generation sequencing technologies are bringing about a renaissance of mining approaches. A comprehensive picture of the genetic landscape of an individual patient will be useful, for example, to identify groups of patients that do or do not respond to certain therapies. The high expectations may however not be satisfied if the number of patient groups with similar characteristics is going to be very large. I therefore doubt that mining sequence data will give us an understanding of why and when therapies work. For understanding the mechanisms underlying diseases, an alternative approach is to model small networks in quantitative mechanistic detail, to elucidate the role of gene and proteins in dynamically changing the functioning of cells. Here an obvious critique is that these models consider too few components, compared to what might be relevant for any particular cell function. I show here that mining approaches and dynamical systems theory are two ends of a spectrum of methodologies to choose from. Drawing upon personal experience in numerous interdisciplinary collaborations, I provide guidance on how to model by discussing the question “Why model?”