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marek ostaszewski

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See detailMetaheuristic Based Clustering Algorithms for Biological Hypergraphs
Changaival, Boonyarit UL; Danoy, Grégoire UL; Ostaszewski, Marek UL et al

in Proceedings of META’2016, 6th International Conference on Metaheuristics and Nature Inspired computing (2016, October 27)

Hypergraphs are widely used for modeling and representing relationships between entities, one such field where their application is prolific is in bioinformatics. In the present era of big data, sizes and ... [more ▼]

Hypergraphs are widely used for modeling and representing relationships between entities, one such field where their application is prolific is in bioinformatics. In the present era of big data, sizes and complexity of these hypergraphs grow exponentially, it is impossible to process them manually or even visualize their interconnectivity superficially. A common approach to tackle their complexity is to cluster similar data nodes together in order to create a more comprehensible representation. This enables similarity discovery and hence, extract hidden knowledge within the hypergraphs. Several state-of-the-art algorithms have been proposed for partitioning and clustering of hypergraphs. Nevertheless, several issues remain unanswered, improvement to existing algorithms are possible, especially in scalability and clustering quality. This article presents a concise survey on hypergraph-clustering algorithms with the emphasis on knowledge-representation in systems biomedicine. It also suggests a novel approach to clustering quality by means of cluster-quality metrics which combines expert knowledge and measurable objective distances in existing biological ontology. [less ▲]

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See detailMINERVA—a platform for visualization and curation of molecular interaction networks
Gawron, Piotr; Ostaszewski, Marek UL; Satagopam, Venkata UL et al

in NPJ Systems Biology and Applications (2016)

Our growing knowledge about various molecular mechanisms is becoming increasingly more structured and accessible. Different repositories of molecular interactions and available literature enable ... [more ▼]

Our growing knowledge about various molecular mechanisms is becoming increasingly more structured and accessible. Different repositories of molecular interactions and available literature enable construction of focused and high-quality molecular interaction networks. Novel tools for curation and exploration of such networks are needed, in order to foster the development of a systems biology environment. In particular, solutions for visualization, annotation and data cross-linking will facilitate usage of network-encoded knowledge in biomedical research. To this end we developed the MINERVA (Molecular Interaction NEtwoRks VisuAlization) platform, a standalone webservice supporting curation, annotation and visualization of molecular interaction networks in Systems Biology Graphical Notation (SBGN)-compliant format. MINERVA provides automated content annotation and verification for improved quality control. The end users can explore and interact with hosted networks, and provide direct feedback to content curators. MINERVA enables mapping drug targets or overlaying experimental data on the visualized networks. Extensive export functions enable downloading areas of the visualized networks as SBGN-compliant models for efficient reuse of hosted networks. The software is available under Affero GPL 3.0 as a Virtual Machine snapshot, Debian package and Docker instance at http://r3lab.uni.lu/web/minerva-website/. We believe that MINERVA is an important contribution to systems biology community, as its architecture enables set-up of locally or globally accessible SBGN-oriented repositories of molecular interaction networks. Its functionalities allow overlay of multiple information layers, facilitating exploration of content and interpretation of data. Moreover, annotation and verification workflows of MINERVA improve the efficiency of curation of networks, allowing life-science researchers to better engage in development and use of biomedical knowledge repositories. [less ▲]

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See detailNeurological Diseases from a Systems Medicine Point of View.
Ostaszewski, Marek UL; Skupin, Alexander UL; Balling, Rudi UL

in Methods in molecular biology (Clifton, N.J.) (2016), 1386

The difficulty to understand, diagnose, and treat neurological disorders stems from the great complexity of the central nervous system on different levels of physiological granularity. The individual ... [more ▼]

The difficulty to understand, diagnose, and treat neurological disorders stems from the great complexity of the central nervous system on different levels of physiological granularity. The individual components, their interactions, and dynamics involved in brain development and function can be represented as molecular, cellular, or functional networks, where diseases are perturbations of networks. These networks can become a useful research tool in investigating neurological disorders if they are properly tailored to reflect corresponding mechanisms. Here, we review approaches to construct networks specific for neurological disorders describing disease-related pathology on different scales: the molecular, cellular, and brain level. We also briefly discuss cross-scale network analysis as a necessary integrator of these scales. [less ▲]

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See detailIntegration and Visualization of Translational Medicine Data for Better Understanding of Human Diseases.
Satagopam, Venkata UL; Gu, Wei UL; Eifes, Serge et al

in Big data (2016), 4(2), 97-108

Translational medicine is a domain turning results of basic life science research into new tools and methods in a clinical environment, for example, as new diagnostics or therapies. Nowadays, the process ... [more ▼]

Translational medicine is a domain turning results of basic life science research into new tools and methods in a clinical environment, for example, as new diagnostics or therapies. Nowadays, the process of translation is supported by large amounts of heterogeneous data ranging from medical data to a whole range of -omics data. It is not only a great opportunity but also a great challenge, as translational medicine big data is difficult to integrate and analyze, and requires the involvement of biomedical experts for the data processing. We show here that visualization and interoperable workflows, combining multiple complex steps, can address at least parts of the challenge. In this article, we present an integrated workflow for exploring, analysis, and interpretation of translational medicine data in the context of human health. Three Web services-tranSMART, a Galaxy Server, and a MINERVA platform-are combined into one big data pipeline. Native visualization capabilities enable the biomedical experts to get a comprehensive overview and control over separate steps of the workflow. The capabilities of tranSMART enable a flexible filtering of multidimensional integrated data sets to create subsets suitable for downstream processing. A Galaxy Server offers visually aided construction of analytical pipelines, with the use of existing or custom components. A MINERVA platform supports the exploration of health and disease-related mechanisms in a contextualized analytical visualization system. We demonstrate the utility of our workflow by illustrating its subsequent steps using an existing data set, for which we propose a filtering scheme, an analytical pipeline, and a corresponding visualization of analytical results. The workflow is available as a sandbox environment, where readers can work with the described setup themselves. Overall, our work shows how visualization and interfacing of big data processing services facilitate exploration, analysis, and interpretation of translational medicine data. [less ▲]

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See detailStaining for unphosphorylated alpha-synuclein in the colon mucosa. No difference between patients with Parkinson's disease and healthy controls
Antony, Paul UL; Antunes, L; Frasquilho, S et al

Scientific Conference (2015, June)

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See detailPlatelet mitochondrial membrane potential in Parkinson's disease.
Antony, Paul UL; Boyd, Olga UL; Trefois, Christophe UL et al

in Annals of clinical and translational neurology (2015), 2(1), 67-73

OBJECTIVE: Mitochondrial dysfunction is a hallmark of idiopathic Parkinson's disease (IPD), which has been reported not to be restricted to striatal neurons. However, studies that analyzed mitochondrial ... [more ▼]

OBJECTIVE: Mitochondrial dysfunction is a hallmark of idiopathic Parkinson's disease (IPD), which has been reported not to be restricted to striatal neurons. However, studies that analyzed mitochondrial function at the level of selected enzymatic activities in peripheral tissues have produced conflicting data. We considered the electron transport chain as a complex system with mitochondrial membrane potential as an integrative indicator for mitochondrial fitness. METHODS: Twenty-five IPD patients (nine females; mean disease duration, 6.2 years) and 16 healthy age-matched controls (12 females) were recruited. Live platelets were purified using magnetic-activated cell sorting (MACS) and single-cell data on mitochondrial membrane potential (Deltapsi) were measured by cytometry and challenged with a protonophore agent. RESULTS: Functional mitochondrial membrane potential was detected in all participants. The challenge test reduced the membrane potential in all IPD patients and controls (P < 0.001). However, the response to the challenge was not significantly different between patients and controls. INTERPRETATION: While the reported protonophore challenge assay is a valid marker of overall mitochondrial function in live platelets, intact mitochondrial membrane potential in platelets derived from IPD patients suggests that presumed mitochondrial enzymatic deficiencies are compensable in this cell type. In consequence, mitochondrial membrane potential in platelets cannot be used as a diagnostic biomarker for nonstratified IPD but should be further explored in potential Parkinson's disease subtypes and tissues with higher energy demands. [less ▲]

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See detailVisualization and Classification of Protein Secondary Structures using Self-Organizing Maps
Grevisse, Christian UL; Muller, Ian William UL; Jimenez Laredo, Juan Luis UL et al

in IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2014) (2014, December)

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See detailCuration of complex molecular pathways of Parkinson's disease as a collaborative scientific community effort
Antony, Paul UL; Ostaszewski, Marek UL; Gawron, P et al

Scientific Conference (2014, June 12)

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See detailIntegrating Pathways of Parkinson's Disease in a Molecular Interaction Map
Fujita, Kazuhiro A.; Ostaszewski, Marek UL; Matsuoka, Yukiko et al

in Molecular Neurobiology (2014)

Parkinson's disease (PD) is a major neurodegenerative chronic disease, most likely caused by a complex interplay of genetic and environmental factors. Information on various aspects of PD pathogenesis is ... [more ▼]

Parkinson's disease (PD) is a major neurodegenerative chronic disease, most likely caused by a complex interplay of genetic and environmental factors. Information on various aspects of PD pathogenesis is rapidly increasing and needs to be efficiently organized, so that the resulting data is available for exploration and analysis. Here we introduce a computationally tractable, comprehensive molecular interaction map of PD. This map integrates pathways implicated in PD pathogenesis such as synaptic and mitochondrial dysfunction, impaired protein degradation, alpha-synuclein pathobiology and neuroinflammation. We also present bioinformatics tools for the analysis, enrichment and annotation of the map, allowing the research community to open new avenues in PD research. The PD map is accessible at http://minerva.uni.lu/pd_map . [less ▲]

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See detailThe Parkinson's Disease Map: A Framework for Integration, Curation and Exploration of Disease-related Pathways
Ostaszewski, Marek UL; Fujita, Kazuhiro; Matsuoka, Yukiko et al

Poster (2013, March 09)

Objectives: The pathogenesis of Parkinson's Disease (PD) is multi-factorial and age-related, implicating various genetic and environmental factors. It becomes increasingly important to develop new ... [more ▼]

Objectives: The pathogenesis of Parkinson's Disease (PD) is multi-factorial and age-related, implicating various genetic and environmental factors. It becomes increasingly important to develop new approaches to organize and explore the exploding knowledge of this field. Methods: The published knowledge on pathways implicated in PD, such as synaptic and mitochondrial dysfunction, alpha-synuclein pathobiology, failure of protein degradation systems and neuroinflammation has been organized and represented using CellDesigner. This repository has been linked to a framework of bioinformatics tools including text mining, database annotation, large-scale data integration and network analysis. The interface for online curation of the repository has been established using Payao tool. Results: We present the PD map, a computer-based knowledge repository, which includes molecular mechanisms of PD in a visually structured and standardized way. A bioinformatics framework that facilitates in-depth knowledge exploration, extraction and curation supports the map. We discuss the insights gained from PD map-driven text mining of a corpus of over 50 thousands full text PD-related papers, integration and visualization of gene expression in post mortem brain tissue of PD patients with the map, as well as results of network analysis. Conclusions: The knowledge repository of disease-related mechanisms provides a global insight into relationships between different pathways and allows considering a given pathology in a broad context. Enrichment with available text and bioinformatics databases as well as integration of experimental data supports better understanding of complex mechanisms of PD and formulation of novel research hypotheses. [less ▲]

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See detailEvolutionary conservation and network structure characterize genes of phenotypic relevance for mitosis in human
Ostaszewski, Marek UL; Eifes, Serge UL; del Sol Mesa, Antonio UL

in PLoS ONE (2012), 7(5), 36488

The impact of gene silencing on cellular phenotypes is difficult to establish due to the complexity of interactions in the associated biological processes and pathways. A recent genome-wide RNA knock-down ... [more ▼]

The impact of gene silencing on cellular phenotypes is difficult to establish due to the complexity of interactions in the associated biological processes and pathways. A recent genome-wide RNA knock-down study both identified and phenotypically characterized a set of important genes for the cell cycle in HeLa cells. Here, we combine a molecular interaction network analysis, based on physical and functional protein interactions, in conjunction with evolutionary information, to elucidate the common biological and topological properties of these key genes. Our results show that these genes tend to be conserved with their corresponding protein interactions across several species and are key constituents of the evolutionary conserved molecular interaction network. Moreover, a group of bistable network motifs is found to be conserved within this network, which are likely to influence the network stability and therefore the robustness of cellular functioning. They form a cluster, which displays functional homogeneity and this cluster is significantly enriched in genes phenotypically relevant for mitosis. Additional results reveal a relationship between specific cellular processes and the phenotypic outcomes induced by gene silencing. This study introduces new ideas regarding the relationship between genotype and phenotype in the context of the cell cycle. We show that the analysis of molecular interaction networks can result in the identification of genes relevant to cellular processes, which is a promising avenue for future research. [less ▲]

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See detailMultiobjective Classification with moGEP: An Application in the Network Traffic Domain
Ostaszewski, Marek UL; Bouvry, Pascal UL; Seredynski, Franciszek

in GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

The paper proposes a multiobjective approach to the problem of malicious network traffic classification, with specificity and sensitivity criteria as objective functions for the problem. The ... [more ▼]

The paper proposes a multiobjective approach to the problem of malicious network traffic classification, with specificity and sensitivity criteria as objective functions for the problem. The multiobjective version of Gene Expression Programming (GEP) called moGEP is proposed and applied to find proper classifiers in the multiobjective search space. The purpose of the classifiers is to discriminate information about the network traffic obtained from Idiotypic Network-based Intrusion Detection System (INIDS), transformed into time series. The proposed approach is validated using the network traffic simulator ns2. Classifiers of high accuracy are obtained and their diversity offers interesting possibilities to the domain of network security. [less ▲]

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See detailNature inspired Algorithm-Based Fault Tolerance on Global Computing Platforms. Application to Symbolic Regression
Varrette, Sébastien UL; Ostaszewski, Marek UL; Bouvry, Pascal UL

in International Conference on Metaheuristics and Nature Inspired Computing (META'08) (2008)

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See detailAn Approach to Intrusion Detection by Means of Idiotypic Networks Paradigm
Ostaszewski, Marek UL; Bouvry, Pascal UL; Seredynski, Franciszek

in IEEE World Congress on Computational Intelligence, WCCI 2008, Congress on Evolutionary Computation CEC 2008, Honk-Kong, June (2008)

In this paper we present a novel intrusion detection architecture based on Idiotypic Network Theory (INIDS), that aims at dealing with large scale network attacks featuring variable properties, like ... [more ▼]

In this paper we present a novel intrusion detection architecture based on Idiotypic Network Theory (INIDS), that aims at dealing with large scale network attacks featuring variable properties, like Denial of Service (DoS). The proposed architecture performs dynamic and adaptive clustering of the network traffic for taking fast and effective countermeasures against such high-volume attacks. INIDS is evaluated on the MITpsila99 dataset and outperforms previous approaches for DoS detection applied to this set. [less ▲]

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See detailAdaptive and Dynamic Intrusion Detection by Means of Idiotypic Networks Paradigm
Ostaszewski, Marek UL; Bouvry, Pascal UL; Seredynski, Franciszek

in The 21th IEEE International Parallel and Distributed Processing Symposium (IPDPS), NIDISC Workshop. (2008)

In this paper we present a novel intrusion detection architecture based on Idiotypic Network Theory (INIDS), that aims at dealing with large scale network attacks featuring variable properties, like ... [more ▼]

In this paper we present a novel intrusion detection architecture based on Idiotypic Network Theory (INIDS), that aims at dealing with large scale network attacks featuring variable properties, like Denial of Service (DoS). The proposed architecture performs dynamic and adaptive clustering of the network traffic for taking fast and effective countermeasures against such high-volume attacks. INIDS is evaluated on the MIT'99 dataset and outperforms previous approaches for DoS detection applied to this set. [less ▲]

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See detailCoevolutionary-based Mechanisms for Network Anomaly Detection
Ostaszewski, Marek UL; Seredynski, Franciszek; Bouvry, Pascal UL

in Journal of Mathematical Modelling and Algorithms (2007), 6(3), 411-431

The paper presents an approach based on the principles of immune systems applied to the anomaly detection problem. Flexibility and efficiency of the anomaly detection system are achieved by building a ... [more ▼]

The paper presents an approach based on the principles of immune systems applied to the anomaly detection problem. Flexibility and efficiency of the anomaly detection system are achieved by building a model of the network behavior based on the self-nonself space paradigm. Covering both self and nonself spaces by hyperrectangular structures is proposed. The structures corresponding to self-space are built using a training set from this space. The hyperrectangular detectors covering nonself space are created using a niching genetic algorithm. A coevolutionary algorithm is proposed to enhance this process. The results of experiments show a high quality of intrusion detection, which outperform the quality of the recently proposed approach based on a hypersphere representation of the self-space. [less ▲]

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