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  • 1
    UID:
    b3kat_BV035282953
    Format: 1 Online-Ressource (X, 430 S.)
    ISBN: 3540601120
    Series Statement: Lecture notes in computer science 946 : Lecture notes in artificial intelligence
    Language: English
    Subjects: Computer Science , Economics
    RVK:
    RVK:
    RVK:
    RVK:
    Keywords: Logischer Schluss ; Unsicherheit ; Logischer Schluss ; Künstliche Intelligenz ; Unvollkommene Information ; Logischer Schluss ; Künstliche Intelligenz ; Fuzzy-Menge ; Unsicheres Schließen ; Konferenzschrift ; Konferenzschrift
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
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  • 2
    UID:
    almahu_BV010229469
    Format: X, 430 S.
    ISBN: 3-540-60112-0
    Series Statement: Lecture notes in computer science 946 : Lecture notes in artificial intelligence
    Language: English
    Subjects: Computer Science , Economics
    RVK:
    RVK:
    RVK:
    RVK:
    RVK:
    Keywords: Logischer Schluss ; Unsicherheit ; Logischer Schluss ; Künstliche Intelligenz ; Unvollkommene Information ; Logischer Schluss ; Künstliche Intelligenz ; Fuzzy-Menge ; Unsicheres Schließen ; Konferenzschrift ; Konferenzschrift ; Konferenzschrift
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  • 3
    UID:
    almahu_9949641784202882
    Format: 1 online resource (276 p.)
    ISBN: 9781394257294 , 1394257295
    Note: Description based upon print version of record. , Chapter 5. Structured Compression of Genetic Information and Genome-Wide Association Study by Additive Models , Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Part 1. Knowledge Integration -- Chapter 1. Clinical Data Warehouses -- 1.1. Introduction to clinical information systems and biomedical warehousing: data warehouses for what purposes? -- 1.1.1. Warehouse history -- 1.1.2. Using data warehouses today -- 1.2. Challenge: widely scattered data -- 1.3. Data warehouses and clinical data -- 1.3.1. Warehouse structures -- 1.3.2. Warehouse construction and supply -- 1.3.3. Uses -- 1.4. Warehouses and omics data: challenges -- 1.4.1. Challenges of data volumetry and structuring omic data , 1.4.2. Attempted solutions -- 1.5. Challenges and prospects -- 1.5.1. Toward general-purpose warehouses -- 1.5.2. Ethical dimension of the implementation and the use of warehouses -- 1.5.3. Origin and reproducibility -- 1.5.4. Data quality -- 1.5.5. Data warehousing federation and data sharing -- 1.6. References -- Chapter 2. Semantic Web Methods for Data Integration in Life Sciences -- 2.1. Data-related requirements in life sciences -- 2.1.1. Databases for the life sciences -- 2.1.2. Requirements -- 2.1.3. Common approaches: InterMine and BioMart -- 2.2. Semantic Web -- 2.2.1. Techniques , 2.2.2. Implementation -- 2.3. Perspectives -- 2.3.1. Facilitating appropriation to users -- 2.3.2. Facilitating the appropriation by software programs: FAIR data -- 2.3.3. Federated queries -- 2.4. Conclusion -- 2.5. References -- Chapter 3. Workflows for Bioinformatics Data Integration -- 3.1. Introduction -- 3.2. Bioinformatics data processing chains: difficulties -- 3.2.1. Designing a data processing chain -- 3.2.2. Analysis execution and reproducibility -- 3.2.3. Maintenance, sharing and reuse -- 3.3. Solutions provided by scientific workflow systems -- 3.3.1. Fundamentals of workflow systems , 3.3.2. Workflow systems -- 3.4. Use case: RNA-seq data analysis -- 3.4.1. Study description -- 3.4.2. From data processing chain to workflows -- 3.4.3. Data processing chains implemented as workflows: conclusion -- 3.5. Challenges, open problems and research opportunities -- 3.5.1. Formalizing workflow development -- 3.5.2. Workflow testing -- 3.5.3. Discovering and sharing workflows -- 3.6. Conclusion -- 3.7. References -- Part 2. Integration and Statistics -- Chapter 4. Variable Selection in the General Linear Model: Application to Multiomic Approaches for the Study of Seed Quality , 4.1. Introduction -- 4.2. Methodology -- 4.2.1. Estimation of the covariance matrix ƒ°q -- 4.2.2. Estimation of B -- 4.3. Numerical experiments -- 4.3.1. Statistical performance -- 4.3.2. Numerical performance -- 4.4. Application to the study of seed quality -- 4.4.1. Metabolomics data -- 4.4.2. Proteomics data -- 4.5. Conclusion -- 4.6. Appendices -- 4.6.1. Example of using the package MultiVarSel for metabolomic data analysis -- 4.6.2. Example of using the package MultiVarSel for proteomic data analysis -- 4.7. Acknowledgments -- 4.8. References
    Additional Edition: Print version: Froidevaux, Christine Biological Data Integration Newark : John Wiley & Sons, Incorporated,c2024
    Language: English
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  • 4
    UID:
    almafu_9961445042002883
    Format: 1 online resource (288 pages)
    ISBN: 9781394257317 , 1394257317
    Series Statement: Computer science. Bioinformatics
    Content: The study of biological data is constantly undergoing profound changes. Firstly, the volume of data available has increased considerably due to new high throughput techniques used for experiments. Secondly, the remarkable progress in both computational and statistical analysis methods and infrastructures has made it possible to process these voluminous data. The resulting challenge concerns our ability to integrate these data, i.e. to use their complementary nature effectively in the hope of advancing our knowledge. Therefore, a major challenge in studying biology today is integrating data for the most exhaustive analysis possible. Biological Data Integration deals in a pedagogical way with research work in biological data science, examining both computational approaches to data integration and statistical approaches to the integration of omics data.
    Note: Preface xi Christine FROIDEVAUX, Marie-Laure MARTIN-MAGNIETTE and Guillem RIGAILL -- Part 1 Knowledge Integration -- Chapter 1 Clinical Data Warehouses 3 Maxime WACK and Bastien RANCE -- 1.1 Introduction to clinical information systems and biomedical warehousing: data warehouses for what purposes? -- 1.1.1 Warehouse history -- 1.1.2 Using data warehouses today -- 1.2 Challenge: widely scattered data -- 1.3 Data warehouses and clinical data -- 1.3.1 Warehouse structures -- 1.3.2 Warehouse construction and supply -- 1.3.3 Uses -- 1.4 Warehouses and omics data: challenges -- 1.4.1 Challenges of data volumetry and structuring omic data -- 1.4.2 Attempted solutions -- 1.5 Challenges and prospects -- 1.5.1 Toward general-purpose warehouses -- 1.5.2 Ethical dimension of the implementation and the use of warehouses -- 1.5.3 Origin and reproducibility -- 1.5.4 Data quality -- 1.5.5 Data warehousing federation and data sharing -- 1.6 References -- Chapter 2 Semantic Web Methods for Data Integration in Life Sciences 25 Olivier DAMERON -- 2.1 Data-related requirements in life sciences -- 2.1.1 Databases for the life sciences -- 2.1.2 Requirements -- 2.1.3 Common approaches: InterMine and BioMart -- 2.2 Semantic Web -- 2.2.1 Techniques -- 2.2.2 Implementation -- 2.3 Perspectives -- 2.3.1 Facilitating appropriation to users -- 2.3.2 Facilitating the appropriation by software programs: FAIR data -- 2.3.3 Federated queries -- 2.4 Conclusion -- 2.5 References -- Chapter 3 Workflows for Bioinformatics Data Integration 53 Sarah COHEN-BOULAKIA and Frédéric LEMOINE -- 3.1 Introduction -- 3.2 Bioinformatics data processing chains: difficulties -- 3.2.1 Designing a data processing chain -- 3.2.2 Analysis execution and reproducibility -- 3.2.3 Maintenance, sharing and reuse -- 3.3 Solutions provided by scientific workflow systems -- 3.3.1 Fundamentals of workflow systems -- 3.3.2 Workflow systems -- 3.4 Use case: RNA-seq data analysis -- 3.4.1 Study description -- 3.4.2 From data processing chain to workflows -- 3.4.3 Data processing chains implemented as workflows: conclusion -- 3.5 Challenges, open problems and research opportunities -- 3.5.1 Formalizing workflow development -- 3.5.2 Workflow testing -- 3.5.3 Discovering and sharing workflows -- 3.6 Conclusion -- 3.7 References -- Part 2 Integration and Statistics -- Chapter 4 Variable Selection in the General Linear Model: Application to Multiomic Approaches for the Study of Seed Quality 89 Céline LÉVY-LEDUC, Marie PERROT-DOCKÈS, Gwendal CUEFF and Loïc RAJJOU -- 4.1 Introduction -- 4.2 Methodology -- 4.2.1 Estimation of the covariance matrix Eq -- 4.2.2 Estimation of B -- 4.3 Numerical experiments -- 4.3.1 Statistical performance -- 4.3.2 Numerical performance -- 4.4 Application to the study of seed quality -- 4.4.1 Metabolomics data -- 4.4.2 Proteomics data -- 4.5 Conclusion -- 4.6 Appendices -- 4.6.1 Example of using the package MultiVarSel for metabolomic data analysis -- 4.6.2 Example of using the package MultiVarSel for proteomic data analysis -- 4.7 Acknowledgments -- 4.8 References -- Chapter 5 Structured Compression of Genetic Information and Genome-Wide Association Study by Additive Models 117 Florent GUINOT, Marie SZAFRANSKI and Christophe AMBROISE -- 5.1 Genome-wide association studies -- 5.1.1 Introduction to genetic mapping and linkage analysis -- 5.1.2 Principles of genome-wide association studies -- 5.1.3 Single nucleotide polymorphism -- 5.1.4 Disease penetrance and odds ratio -- 5.1.5 Single marker analysis -- 5.1.6 Multi-marker analysis -- 5.2 Structured compression and association study -- 5.2.1 Context -- 5.2.2 New structured compression approach -- 5.3 Application to ankylosing spondylitis (AS) -- 5.3.1 Data -- 5.3.2 Predictive power evaluation -- 5.3.3 Manhattan diagram -- 5.3.4 Estimation for the most significant SNP aggregates -- 5.4 Conclusion -- 5.5 References -- Chapter 6 Kernels for Omics 151 Jérôme MARIETTE and Nathalie VIALANEIX -- 6.1 Introduction -- 6.2 Relational data -- 6.2.1 Data described by the kernel -- 6.2.2 Data described by a general (dis)similarity measure -- 6.3 Exploratory analysis for relational data -- 6.3.1 Kernel clustering -- 6.3.2 Kernel principal component analysis -- 6.3.3 Kernel self-organizing maps -- 6.3.4 Limitations of relational methods -- 6.4 Combining relational data -- 6.4.1 Data integration in systems biology -- 6.4.2 Kernel approaches in data integration -- 6.4.3 A consensual kernel -- 6.4.4 A parsimonious kernel that preserves the topology of the initial data -- 6.4.5 A complete kernel preserving the topology of the initial data -- 6.5 Application -- 6.5.1 Loading Tara Ocean data -- 6.5.2 Data integration by kernel approaches -- 6.5.3 Exploratory analysis: kernel PCA -- 6.6 Session information for the results of the example -- 6.7 References -- Chapter 7 Multivariate Models for Data Integration and Biomarker Selection in 'Omics Data 195 Sébastien DÉJEAN and Kim-Anh LÊ CAO -- 7.1 Introduction -- 7.2 Background -- 7.2.1 Mathematical notations -- 7.2.2 Terminology -- 7.2.3 Multivariate projection-based approaches -- 7.2.4 A criterion to maximize specific to each methodology -- 7.2.5 A linear combination of variables to reduce the dimension of the data -- 7.2.6 Identifying a subset of relevant molecular features -- 7.2.7 Summary -- 7.3 From the biological question to the statistical analysis -- 7.3.1 Exploration of one dataset: PCA -- 7.3.2 Classify samples: projection to latent structure discriminant analysis -- 7.3.3 Integration of two datasets: projection to latent structure and related methods -- 7.3.4 Integration of several datasets: multi-block approaches -- 7.4 Graphical outputs -- 7.4.1 Individual plots -- 7.4.2 Variable plots -- 7.5 Overall summary -- 7.6 Liver toxicity study -- 7.6.1 The datasets -- 7.6.2 Biological questions and statistical methods -- 7.6.3 Single dataset analysis -- 7.6.4 Integrative analysis -- 7.7 Conclusion -- 7.8 Acknowledgments -- 7.9 Appendix: reproducible R code -- 7.9.1 Toy examples -- 7.9.2 Liver toxicity -- 7.10 References -- List of Authors -- Index.
    Language: English
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  • 5
    UID:
    almafu_9959186471402883
    Format: 1 online resource (X, 438 p.)
    Edition: 1st ed. 1995.
    Edition: Online edition Springer Lecture Notes Archive ; 041142-5
    ISBN: 3-540-49438-3
    Series Statement: Lecture Notes in Artificial Intelligence ; 946
    Content: This volume constitutes the 48 full refereed research papers accepted for presentation at the Third European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty, ECSQARU '95, held in Fribourg, Switzerland in July 1995 under the sponsorship of the DRUMS consortium (ESPRIT II BRA 6156). In recent years, it has become apparent that an important part of the theory of AI is concerned with reasoning on the basis of uncertain, vague, incomplete, or inconsistent information. A variety of nonclassical formalisms, both symbolic and numerical, have been developed and are addressed in this volume; among them are nonmonotonic and modal logics, fuzzy sets, possibility theory, believe functions, evidence theory, dynamic models, and Bayesian networks.
    Note: Bibliographic Level Mode of Issuance: Monograph , For all typical -- A posteriori knowledge: from ambiguous knowledge and undefined information to knowledge -- Modeling uncertain relational knowledge: the AV-quantified production rules approach -- Multiple database logic -- A local approach to reasoning under inconsistency in stratified knowledge bases -- Quasi-classical logic: Non-trivializable classical reasoning from inconsistent information -- A cost bounded possibilistic ATMS -- A substructural connective for possibilistic logic -- Chain graphs: Semantics and expressiveness -- Axiomatic treatment of possibilistic independence -- Parametric structure of probabilities in Bayesian networks -- From non-monotonic syntax-based entailment to preference-based argumentation -- Non-monotonic syntax-based entailment: A classification of consequence relations -- Local Möbius transforms of monotone capacities -- Automated reasoning with merged contradictory information whose reliability depends on topics -- Linking transition-based update and base revision -- Prioritized transitions for updates -- Probabilistic satisfiability and decomposition -- Update postulates without inertia -- Similarity-based consequence relations -- Epistemic approach to actions with typical effects -- Nonmonotonic belief state frames and reasoning frames -- A Bayesian network based learning system: — Architecture and performance comparison with other methods -- Specificity by default -- Constructing flexible dynamic belief networks from first-order probabilistic knowledge bases -- On the formalism of stochastic logic -- Using default logic in information retrieval -- Sensitivity analysis in Bayesian networks -- Bayesian approximation and invariance of Bayesian belief functions -- Model-based diagnostics using hints -- An axiomatic approach to extensional probability measures -- The dynamics of default reasoning -- Lemma handling in default logic theorem provers -- Uncertain reasoning in concept lattices -- A theorem prover for default logic based on prioritized conflict resolution and an extended resolution principle -- A theorem prover for lukaszewicz open default theory -- Two different types of discontinuity of bayesian learning in causal probabilistic networks -- Revision in extended propositional calculus -- Using qualitative uncertainty in protein topology prediction -- Circumscribing features and fluents: Reasoning about action with default effects -- Using Maximum Entropy to compute marginal probabilities in a causal binary tree need not take exponential time -- Yet some more considerations on cumulativity in default logics -- A two-stage approach to first order default reasoning -- A reduction of the theory of confirmation to the notions of distance and measure -- Cluster-based specification techniques in Dempster-Shafer theory -- And/or trees for knowledge representation -- Why defeasible deontic logic needs a multi preference semantics -- Numeric defaults. , English
    In: Springer eBooks
    Additional Edition: ISBN 3-540-60112-0
    Language: English
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  • 6
    UID:
    almahu_9947920621402882
    Format: X, 438 p. , online resource.
    ISBN: 9783540494386
    Series Statement: Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 946
    Content: This volume constitutes the 48 full refereed research papers accepted for presentation at the Third European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty, ECSQARU '95, held in Fribourg, Switzerland in July 1995 under the sponsorship of the DRUMS consortium (ESPRIT II BRA 6156). In recent years, it has become apparent that an important part of the theory of AI is concerned with reasoning on the basis of uncertain, vague, incomplete, or inconsistent information. A variety of nonclassical formalisms, both symbolic and numerical, have been developed and are addressed in this volume; among them are nonmonotonic and modal logics, fuzzy sets, possibility theory, believe functions, evidence theory, dynamic models, and Bayesian networks.
    Note: For all typical -- A posteriori knowledge: from ambiguous knowledge and undefined information to knowledge -- Modeling uncertain relational knowledge: the AV-quantified production rules approach -- Multiple database logic -- A local approach to reasoning under inconsistency in stratified knowledge bases -- Quasi-classical logic: Non-trivializable classical reasoning from inconsistent information -- A cost bounded possibilistic ATMS -- A substructural connective for possibilistic logic -- Chain graphs: Semantics and expressiveness -- Axiomatic treatment of possibilistic independence -- Parametric structure of probabilities in Bayesian networks -- From non-monotonic syntax-based entailment to preference-based argumentation -- Non-monotonic syntax-based entailment: A classification of consequence relations -- Local Möbius transforms of monotone capacities -- Automated reasoning with merged contradictory information whose reliability depends on topics -- Linking transition-based update and base revision -- Prioritized transitions for updates -- Probabilistic satisfiability and decomposition -- Update postulates without inertia -- Similarity-based consequence relations -- Epistemic approach to actions with typical effects -- Nonmonotonic belief state frames and reasoning frames -- A Bayesian network based learning system: — Architecture and performance comparison with other methods -- Specificity by default -- Constructing flexible dynamic belief networks from first-order probabilistic knowledge bases -- On the formalism of stochastic logic -- Using default logic in information retrieval -- Sensitivity analysis in Bayesian networks -- Bayesian approximation and invariance of Bayesian belief functions -- Model-based diagnostics using hints -- An axiomatic approach to extensional probability measures -- The dynamics of default reasoning -- Lemma handling in default logic theorem provers -- Uncertain reasoning in concept lattices -- A theorem prover for default logic based on prioritized conflict resolution and an extended resolution principle -- A theorem prover for lukaszewicz open default theory -- Two different types of discontinuity of bayesian learning in causal probabilistic networks -- Revision in extended propositional calculus -- Using qualitative uncertainty in protein topology prediction -- Circumscribing features and fluents: Reasoning about action with default effects -- Using Maximum Entropy to compute marginal probabilities in a causal binary tree need not take exponential time -- Yet some more considerations on cumulativity in default logics -- A two-stage approach to first order default reasoning -- A reduction of the theory of confirmation to the notions of distance and measure -- Cluster-based specification techniques in Dempster-Shafer theory -- And/or trees for knowledge representation -- Why defeasible deontic logic needs a multi preference semantics -- Numeric defaults.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783540601128
    Language: English
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  • 7
    UID:
    almahu_9948621044202882
    Format: X, 438 p. , online resource.
    Edition: 1st ed. 1995.
    ISBN: 9783540494386
    Series Statement: Lecture Notes in Artificial Intelligence ; 946
    Content: This volume constitutes the 48 full refereed research papers accepted for presentation at the Third European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty, ECSQARU '95, held in Fribourg, Switzerland in July 1995 under the sponsorship of the DRUMS consortium (ESPRIT II BRA 6156). In recent years, it has become apparent that an important part of the theory of AI is concerned with reasoning on the basis of uncertain, vague, incomplete, or inconsistent information. A variety of nonclassical formalisms, both symbolic and numerical, have been developed and are addressed in this volume; among them are nonmonotonic and modal logics, fuzzy sets, possibility theory, believe functions, evidence theory, dynamic models, and Bayesian networks.
    Note: For all typical -- A posteriori knowledge: from ambiguous knowledge and undefined information to knowledge -- Modeling uncertain relational knowledge: the AV-quantified production rules approach -- Multiple database logic -- A local approach to reasoning under inconsistency in stratified knowledge bases -- Quasi-classical logic: Non-trivializable classical reasoning from inconsistent information -- A cost bounded possibilistic ATMS -- A substructural connective for possibilistic logic -- Chain graphs: Semantics and expressiveness -- Axiomatic treatment of possibilistic independence -- Parametric structure of probabilities in Bayesian networks -- From non-monotonic syntax-based entailment to preference-based argumentation -- Non-monotonic syntax-based entailment: A classification of consequence relations -- Local Möbius transforms of monotone capacities -- Automated reasoning with merged contradictory information whose reliability depends on topics -- Linking transition-based update and base revision -- Prioritized transitions for updates -- Probabilistic satisfiability and decomposition -- Update postulates without inertia -- Similarity-based consequence relations -- Epistemic approach to actions with typical effects -- Nonmonotonic belief state frames and reasoning frames -- A Bayesian network based learning system: - Architecture and performance comparison with other methods -- Specificity by default -- Constructing flexible dynamic belief networks from first-order probabilistic knowledge bases -- On the formalism of stochastic logic -- Using default logic in information retrieval -- Sensitivity analysis in Bayesian networks -- Bayesian approximation and invariance of Bayesian belief functions -- Model-based diagnostics using hints -- An axiomatic approach to extensional probability measures -- The dynamics of default reasoning -- Lemma handling in default logic theorem provers -- Uncertain reasoning in concept lattices -- A theorem prover for default logic based on prioritized conflict resolution and an extended resolution principle -- A theorem prover for lukaszewicz open default theory -- Two different types of discontinuity of bayesian learning in causal probabilistic networks -- Revision in extended propositional calculus -- Using qualitative uncertainty in protein topology prediction -- Circumscribing features and fluents: Reasoning about action with default effects -- Using Maximum Entropy to compute marginal probabilities in a causal binary tree need not take exponential time -- Yet some more considerations on cumulativity in default logics -- A two-stage approach to first order default reasoning -- A reduction of the theory of confirmation to the notions of distance and measure -- Cluster-based specification techniques in Dempster-Shafer theory -- And/or trees for knowledge representation -- Why defeasible deontic logic needs a multi preference semantics -- Numeric defaults.
    In: Springer Nature eBook
    Additional Edition: Printed edition: ISBN 9783662202029
    Additional Edition: Printed edition: ISBN 9783540601128
    Language: English
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  • 8
    UID:
    almahu_9947364047902882
    Format: XIII, 209 p. , online resource.
    ISBN: 9783540698289
    Series Statement: Lecture Notes in Computer Science, 5109
    Content: This book constitutes the refereed proceedings of the 5th International Workshop on Data Integration in the Life Sciences, DILS 2008, held in Evry, France in June 2008. The 18 revised full papers presented together with 3 keynote talks and a tutorial paper were carefully reviewed and selected from 54 submissions. The papers adress all current issues in data integration and data management from the life science point of view and are organized in topical sections on Semantic Web for the life sciences, designing and evaluating architectures to integrate biological data, new architectures and experience on using systems, systems using technologies from the Semantic Web for the life sciences, mining integrated biological data, and new features of major resources for biomolecular data.
    Note: Keynote Presentations -- Ontologies and Data Integration in Biomedicine: Success Stories and Challenging Issues -- BioWarehouse: Relational Integration of Eleven Bioinformatics Databases and Formats -- Data Integration in the Life Sciences: Fun, Findings and Frustrations -- Semantic Web for the Life Sciences -- Analyzing the Evolution of Life Science Ontologies and Mappings -- Ontology Design Principles and Normalization Techniques in the Web -- Exploiting Ontology Structure and Patterns of Annotation to Mine Significant Associations between Pairs of Controlled Vocabulary Terms -- Designing and Evaluating Architectures to Integrate Biological Data -- Automatic Methods for Integrating Biomedical Data Sources in a Mediator-Based System -- VisGenome and Ensembl: Usability of Integrated Genome Maps -- An Entity Resolution Framework for Deduplicating Proteins -- New Architectures and Experience on Using Systems -- Semantic Representation and Querying of caBIG Data Services -- SisGen: A CORBA–Based Data Management Program for DNA Sequencing Projects -- Bgee: Integrating and Comparing Heterogeneous Transcriptome Data Among Species -- ENFIN - An Integrative Structure for Systems Biology -- Systems Using Technologies from the Semantic Web for the Life Sciences -- A System for Ontology-Based Annotation of Biomedical Data -- Bio2RDF : A Semantic Web Atlas of Post Genomic Knowledge about Human and Mouse -- OMIE: Ontology Mapping within an Interactive and Extensible Environment -- Chemical Knowledge for the Semantic Web -- Mining Integrated Biological Data -- Combining One-Class Classification Models Based on Diverse Biological Data for Prediction of Protein-Protein Interactions -- Semi Supervised Spectral Clustering for Regulatory Module Discovery -- New Features of Major Resources for Biomolecular Data -- UniProtKB/Swiss-Prot: New and Future Developments -- EBI Proteomics Services -- DILS 2008 Tutorial -- Bio-ontologies Tutorial.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783540698272
    Language: English
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  • 9
    UID:
    edoccha_9959186471402883
    Format: 1 online resource (X, 438 p.)
    Edition: 1st ed. 1995.
    Edition: Online edition Springer Lecture Notes Archive ; 041142-5
    ISBN: 3-540-49438-3
    Series Statement: Lecture Notes in Artificial Intelligence ; 946
    Content: This volume constitutes the 48 full refereed research papers accepted for presentation at the Third European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty, ECSQARU '95, held in Fribourg, Switzerland in July 1995 under the sponsorship of the DRUMS consortium (ESPRIT II BRA 6156). In recent years, it has become apparent that an important part of the theory of AI is concerned with reasoning on the basis of uncertain, vague, incomplete, or inconsistent information. A variety of nonclassical formalisms, both symbolic and numerical, have been developed and are addressed in this volume; among them are nonmonotonic and modal logics, fuzzy sets, possibility theory, believe functions, evidence theory, dynamic models, and Bayesian networks.
    Note: Bibliographic Level Mode of Issuance: Monograph , For all typical -- A posteriori knowledge: from ambiguous knowledge and undefined information to knowledge -- Modeling uncertain relational knowledge: the AV-quantified production rules approach -- Multiple database logic -- A local approach to reasoning under inconsistency in stratified knowledge bases -- Quasi-classical logic: Non-trivializable classical reasoning from inconsistent information -- A cost bounded possibilistic ATMS -- A substructural connective for possibilistic logic -- Chain graphs: Semantics and expressiveness -- Axiomatic treatment of possibilistic independence -- Parametric structure of probabilities in Bayesian networks -- From non-monotonic syntax-based entailment to preference-based argumentation -- Non-monotonic syntax-based entailment: A classification of consequence relations -- Local Möbius transforms of monotone capacities -- Automated reasoning with merged contradictory information whose reliability depends on topics -- Linking transition-based update and base revision -- Prioritized transitions for updates -- Probabilistic satisfiability and decomposition -- Update postulates without inertia -- Similarity-based consequence relations -- Epistemic approach to actions with typical effects -- Nonmonotonic belief state frames and reasoning frames -- A Bayesian network based learning system: — Architecture and performance comparison with other methods -- Specificity by default -- Constructing flexible dynamic belief networks from first-order probabilistic knowledge bases -- On the formalism of stochastic logic -- Using default logic in information retrieval -- Sensitivity analysis in Bayesian networks -- Bayesian approximation and invariance of Bayesian belief functions -- Model-based diagnostics using hints -- An axiomatic approach to extensional probability measures -- The dynamics of default reasoning -- Lemma handling in default logic theorem provers -- Uncertain reasoning in concept lattices -- A theorem prover for default logic based on prioritized conflict resolution and an extended resolution principle -- A theorem prover for lukaszewicz open default theory -- Two different types of discontinuity of bayesian learning in causal probabilistic networks -- Revision in extended propositional calculus -- Using qualitative uncertainty in protein topology prediction -- Circumscribing features and fluents: Reasoning about action with default effects -- Using Maximum Entropy to compute marginal probabilities in a causal binary tree need not take exponential time -- Yet some more considerations on cumulativity in default logics -- A two-stage approach to first order default reasoning -- A reduction of the theory of confirmation to the notions of distance and measure -- Cluster-based specification techniques in Dempster-Shafer theory -- And/or trees for knowledge representation -- Why defeasible deontic logic needs a multi preference semantics -- Numeric defaults. , English
    In: Springer eBooks
    Additional Edition: ISBN 3-540-60112-0
    Language: English
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  • 10
    UID:
    kobvindex_ZLB12373799
    Format: X, 430 Seiten , graph. Darst. , 24 cm
    Edition: 1
    ISBN: 3540601120
    Series Statement: Lecture notes in computer science 946
    Note: Literaturangaben
    Language: English
    Keywords: Unsicheres Schließen ; Kongress ; Freiburg 〈Üechtland, 1995〉 ; Unsicheres Schließen ; Kongress ; Freiburg im Üechtland 〈1995〉 ; Kongress
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