Search results for "Biological network"

showing 10 items of 32 documents

Knowledge Extraction from Biological and Social Graphs

2022

Many problems from real life deal with the generation of enormous, varied, dynamic, and interconnected datasets coming from different and heterogeneous sources. Analysing large volumes of data makes it possible to generate new knowledge useful for making more informed decisions, in business and beyond. From personalising customer communication to streamlining production processes, via flow and emergency management, Big Data Analytics has an impact on all processes. The potential uses of Big Data go much further: two of the largest sources of data are including individual traders’ purchasing history, the use of Biological Networks for disease prediction or the reduction and study of Biologic…

Social networkBig dataBiological network
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Algorithms and tools for protein-protein interaction networks clustering, with a special focus on population-based stochastic methods

2014

Abstract Motivation: Protein–protein interaction (PPI) networks are powerful models to represent the pairwise protein interactions of the organisms. Clustering PPI networks can be useful for isolating groups of interacting proteins that participate in the same biological processes or that perform together specific biological functions. Evolutionary orthologies can be inferred this way, as well as functions and properties of yet uncharacterized proteins. Results: We present an overview of the main state-of-the-art clustering methods that have been applied to PPI networks over the past decade. We distinguish five specific categories of approaches, describe and compare their main features and …

Statistics and ProbabilityComputer sciencePopulationPopulation basedMachine learningcomputer.software_genreBiochemistryProtein protein interaction networkgenetic algorithmsProtein–protein interactionBioinformatics Clustering Biological NetworksPPI networkscomplex detectionProtein Interaction MappingAnimalsCluster AnalysisHumanseducationCluster analysisMolecular BiologyTopology (chemistry)Class (computer programming)education.field_of_studybusiness.industryfood and beveragesProteinsComputer Science ApplicationsComputational MathematicsComputational Theory and MathematicsArtificial intelligenceData miningbusinessFocus (optics)computerAlgorithms
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Textual data compression in computational biology: a synopsis.

2009

Abstract Motivation: Textual data compression, and the associated techniques coming from information theory, are often perceived as being of interest for data communication and storage. However, they are also deeply related to classification and data mining and analysis. In recent years, a substantial effort has been made for the application of textual data compression techniques to various computational biology tasks, ranging from storage and indexing of large datasets to comparison and reverse engineering of biological networks. Results: The main focus of this review is on a systematic presentation of the key areas of bioinformatics and computational biology where compression has been use…

Statistics and ProbabilityDatabases Factualbusiness.industryComputer sciencemedia_common.quotation_subjectSearch engine indexingcompression dataComputational BiologyInformation Storage and RetrievalComputational biologyBiochemistryData scienceComputer Science ApplicationsComputational MathematicsPresentationSoftwareComputational Theory and MathematicsBenchmark (computing)businessMolecular BiologyBiological networkSoftwareData compressionmedia_commonBioinformatics (Oxford, England)
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Complex Detection in Protein-Protein Interaction Networks: A Compact Overview for Researchers and Practitioners

2012

The availability of large volumes of protein-protein interaction data has allowed the study of biological networks to unveil the complex structure and organization in the cell. It has been recognized by biologists that proteins interacting with each other often participate in the same biological processes, and that protein modules may be often associated with specific biological functions. Thus the detection of protein complexes is an important research problem in systems biology. In this review, recent graph-based approaches to clustering protein interaction networks are described and classified with respect to common peculiarities. The goal is that of providing a useful guide and referenc…

Structure (mathematical logic)Computer scienceSystems biologyCellData ScienceNanotechnologyComputational biologyProtein protein interaction networkBioinformatics network analysismedicine.anatomical_structuremedicineGraph (abstract data type)Lecture Notes in Computer ScienceCluster analysisProtein modulesBiological network
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"Master-Slave" Biological Network Alignment

2010

Performing global alignment between protein-protein interaction (PPI) networks of different organisms is important to infer knowledge about conservation across species. Known methods that perform this task operate symmetrically, that is to say, they do not assign a distinct role to the input PPI networks. However, in most cases, the input networks are indeed distinguishable on the basis of how well the corresponding organism is biologically well-characterized. For well-characterized organisms the associated PPI network supposedly encode in a sound manner all the information about their proteins and associated interactions, which is far from being the case for not well characterized ones. He…

Theoretical computer scienceBasis (linear algebra)business.industryComputer scienceFingerprint (computing)Process (computing)Master/slaveENCODETask (computing)Bioinformatics network analysisArtificial intelligencebusinessBiological networkOrganism
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Network Centralities and Node Ranking

2017

An important problem in network analysis is understanding how much nodes are important in order to “propagate” the information across the input network. To this aim, many centrality measures have been proposed in the literature and our main goal here is that of providing an overview of the most important of them. In particular, we distinguish centrality measures based on walks computation from those based on shortest-paths computation. We also provide some examples in order to clarify how these measures can be calculated, with special attention to Degree Centrality, Closeness Centrality and Betweennes Centrality.

Theoretical computer scienceCentrality measureNetwork topologyShortest pathSettore INF/01 - InformaticaComputer scienceBiological networkComputationNode (networking)Network topologySubgraph extractionNode centralityRankingShortest path problemCentralityBiological networkNetwork analysisNode neighborhoodNode ranking
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Problems and Techniques

2017

When biological networks are considered, the extraction of interesting knowledge often involves subgraphs isomorphism check that is known to be NP-complete. For this reason, many approaches try to simplify the problem under consideration by considering structures simpler than graphs, such as trees or paths. Furthermore, the number of existing approximate techniques is notably greater than the number of exact methods. In this chapter, we provide an overview of three important problems defined on biological networks: network alignment, network clustering, and motifs extraction from biological networks. For each of these problems, we also describe some of the most important techniques proposed…

Theoretical computer scienceCommunity searchComputer scienceGraph alignmentNetwork alignmentNetwork clusteringIsomorphismBiological network
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Asymmetric Comparison and Querying of Biological Networks

2011

Comparing and querying the protein-protein interaction (PPI) networks of different organisms is important to infer knowledge about conservation across species. Known methods that perform these tasks operate symmetrically, i.e., they do not assign a distinct role to the input PPI networks. However, in most cases, the input networks are indeed distinguishable on the basis of how the corresponding organism is biologically well characterized. In this paper a new idea is developed, that is, to exploit differences in the characterization of organisms at hand in order to devise methods for comparing their PPI networks. We use the PPI network (called Master) of the best characterized organism as a …

Theoretical computer scienceFinite-state machineMatching (graph theory)Computer scienceApplied MathematicsFingerprint (computing)Process (computing)Computational BiologyViterbi algorithmModels BiologicalAutomatonBioinformatics network analysissymbols.namesakeSequence Analysis ProteinLinearizationProtein Interaction MappingGeneticssymbolsProtein Interaction Domains and MotifsSequence AlignmentAlgorithmsBiological networkBiotechnologyIEEE/ACM Transactions on Computational Biology and Bioinformatics
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Approximate Matching over Biological RDF Graphs

2012

In the last few years, the amount of biological interaction data discovered and stored in public databases (e.g., KEGG [2]) considerably increased. To this aim, RDF is a powerful representation for interactions (or pathways), since they can be modeled as directed graphs, often referred to as biological networks, where nodes represent cellular components and the (labeled or unlabeled) edges correspond to interactions among components. Often for a given organism some components are known to be linked by well studied interactions. Such groups of components are called modules and they can be represented by sub-graphs in the corresponding biological network model. At today, one of the most impor…

Theoretical computer scienceGraph databaseComputer scienceSearch engine indexingcomputer.file_formatcomputer.software_genreGraphBioinformatics network analysisApproximate matchingIsomorphismRDFKEGGHeuristicscomputerBiological networkNetwork analysis
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Biologically inspired information processing and synchronization in ensembles of non-identical threshold-potential nanostructures.

2013

Nanotechnology produces basic structures that show a significant variability in their individual physical properties. This experimental fact may constitute a serious limitation for most applications requiring nominally identical building blocks. On the other hand, biological diversity is found in most natural systems. We show that reliable information processing can be achieved with heterogeneous groups of non-identical nanostructures by using some conceptual schemes characteristic of biological networks (diversity, frequency-based signal processing, rate and rank order coding, and synchronization). To this end, we simulate the integrated response of an ensemble of single-electron transisto…

Time FactorsTransistors ElectronicScienceMaterials ScienceMonte Carlo methodSynchronizationMaterial by AttributeSet (abstract data type)BiomimeticsImage Processing Computer-AssistedNanotechnologyBiologyNanomaterialsComputational NeurosciencePhysicsCoding MechanismsSignal processingMultidisciplinaryQInformation processingRComputational BiologySignal Processing Computer-AssistedSensory SystemsNanostructuresBionanotechnologyElectronic MaterialsProbability distributionMedicineBiological systemMonte Carlo MethodRealization (systems)Biological networkResearch ArticleBiotechnologyNeurosciencePLoS ONE
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