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[null,"1.","Record Nr.",null,"UNINA9910450670003321"]
[null,null,"Autore",null,"McGrath Kevin"]
[null,null,"Titolo",null,"The Sanskrit hero [[electronic resource] ] : Karṇa in epic Mahābhārata / / by Kevin McGrath"]
[null,null,"Pubbl/distr/stampa",null,"Leiden ; ; Boston, : Brill, 2004"]
[null,null,"ISBN",null,"1-280-91490-4"]
[{"$nulls":4},"9786610914906"]
[{"$nulls":4},"90-474-0492-0"]
[{"$nulls":4},"1-4294-1477-4"]
[null,null,"Descrizione fisica",null,"1 online resource (273 p.)"]
[null,null,"Collana",null,"Brill's Indological library, , 0925-2916 ; ; v. 20"]
[null,null,"Disciplina",null,"294.5/923046"]
[null,null,"Soggetti",null,"Karṇa (Hindu mythology) in literature"]
[{"$nulls":4},"Epic literature, Sanskrit - History and criticism"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Bibliographic Level Mode of Issuance: Monograph"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (p. [247]-258) and index."]
[null,"2.","Record Nr.",null,"UNINA9910143713103321"]
[null,null,"Titolo",null,"Data analysis and visualization in genomics and proteomics [[electronic resource] /] / editors, Francisco Azuaje and Joaquín Dopazo"]
[null,null,"Pubbl/distr/stampa",null,"Hoboken, NJ, : John Wiley, c2005"]
[null,null,"ISBN",null,"1-280-27600-2"]
[{"$nulls":4},"9786610276004"]
[{"$nulls":4},"0-470-09441-9"]
[{"$nulls":4},"0-470-09440-0"]
[null,null,"Descrizione fisica",null,"1 online resource (285 p.)"]
[null,null,"Disciplina",null,"372.860285"]
[{"$nulls":4},"572.8/6"]
[null,null,"Soggetti",null,"Genomics - Data processing"]
[{"$nulls":4},"Proteomics - Data processing"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Data Analysis and Visualization in Genomics and Proteomics; Contents; Preface; List of Contributors; SECTION I INTRODUCTION - DATA DIVERSITY AND INTEGRATION; 1 Integrative Data Analysis and Visualization: Introduction to Critical Problems, Goals and Challenges; 1.1 Data Analysis and Visualization: An Integrative Approach; 1.2 Critical Design and Implementation Factors; 1.3 Overview of Contributions; References; 2 Biological Databases: Infrastructure, Content and Integration; 2.1 Introduction; 2.2 Data Integration; 2.3 Review of Molecular Biology Databases; 2.4 Conclusion; References"]
[{"$nulls":4},"3 Data and Predictive Model Integration: an Overview of Key Concepts, Problems and Solutions3.1 Integrative Data Analysis and Visualization: Motivation and Approaches; 3.2 Integrating Informational Views and Complexity for Understanding Function; 3.3 Integrating Data Analysis Techniques for Supporting Functional Analysis; 3.4 Final Remarks; References; SECTION II INTEGRATIVE DATA MINING AND VISUALIZATION - EMPHASIS ON COMBINATION OF MULTIPLE DATA TYPES; 4 Applications of Text Mining in Molecular Biology, from Name Recognition to Protein Interaction Maps; 4.1 Introduction"]
[{"$nulls":4},"4.2 Introduction to Text Mining and NLP4.3 Databases and Resources "]
[{"$nulls":4},"for Biomedical Text Mining; 4.4 Text Mining and Protein-Protein Interactions; 4.5 Other Text-Mining Applications in Genomics; 4.6 The Future of NLP in Biomedicine; Acknowledgements; References; 5 Protein Interaction Prediction by Integrating Genomic Features and Protein Interaction Network Analysis; 5.1 Introduction; 5.2 Genomic Features in Protein Interaction Predictions; 5.3 Machine Learning on Protein-Protein Interactions; 5.4 The Missing Value Problem; 5.5 Network Analysis of Protein Interactions; 5.6 Discussion"]
[{"$nulls":4},"References6 Integration of Genomic and Phenotypic Data; 6.1 Phenotype; 6.2 Forward Genetics and QTL Analysis; 6.3 Reverse Genetics; 6.4 Prediction of Phenotype from Other Sources of Data; 6.5 Integrating Phenotype Data with Systems Biology; 6.6 Integration of Phenotype Data in Databases; 6.7 Conclusions; References; 7 Ontologies and Functional Genomics; 7.1 Information Mining in Genome-Wide Functional Analysis; 7.2 Sources of Information: Free Text Versus Curated Repositories; 7.3 Bio-Ontologies and the Gene Ontology in Functional Genomics"]
[{"$nulls":4},"7.4 Using GO to Translate the Results of Functional Genomic Experiments into Biological Knowledge7.5 Statistical Approaches to Test Significant Biological Differences; 7.6 Using FatiGO to Find Significant Functional Associations in Clusters of Genes; 7.7 Other Tools; 7.8 Examples of Functional Analysis of Clusters of Genes; 7.9 Future Prospects; References; 8 The C. elegans Interactome: its Generation and Visualization; 8.1 Introduction; 8.2 The ORFeome: the first step toward the interactome of C. elegans"]
[{"$nulls":4},"8.3 Large-Scale High-Throughput Yeast Two-Hybrid Screens to Map the C. elegans Protein-Protein Interaction (Interactome) Network: Technical Aspects"]
[null,null,null,"Sommario/riassunto","Data Analysis and Visualization in Genomics and Proteomics is the first book addressing integrative data analysis and visualization in this field. It addresses important techniques for the interpretation of data originating from multiple sources, encoded in different formats or protocols, and processed by multiple systems. One of the first systematic overviews of the problem of biological data integration using computational approachesThis book provides scientists and students with the basis for the development and application of integrative computational met"]
[null,"3.","Record Nr.",null,"UNINA9910784306903321"]
[null,null,"Autore",null,"Box-Steffensmeier Janet M. <1965->"]
[null,null,"Titolo",null,"Event history modeling : a guide for social scientists / / Janet M. Box-Steffensmeier, Bradford S. Jones [[electronic resource]]"]
[null,null,"Pubbl/distr/stampa",null,"Cambridge : , : Cambridge University Press, , 2004"]
[null,null,"ISBN",null,"1-107-15042-6"]
[{"$nulls":4},"1-280-47751-2"]
[{"$nulls":4},"0-511-79087-2"]
[{"$nulls":4},"0-511-19543-5"]
[{"$nulls":4},"0-511-19609-1"]
[{"$nulls":4},"0-511-19405-6"]
[{"$nulls":4},"0-511-31441-8"]
[{"$nulls":4},"0-511-19479-X"]
[null,null,"Descrizione fisica",null,"1 online resource (xiii, 218 pages) : digital, PDF file(s)"]
[null,null,"Collana",null,"Analytical methods for social research"]
[null,null,"Disciplina",null,"001.4/32"]
[null,null,"Soggetti",null,"Event history analysis - Computer simulation"]
[{"$nulls":4},"Social sciences - Methodology"]
[{"$nulls":4},"History - Methodology"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Title from publisher's bibliographic system (viewed on 05 Oct 2015)."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (p. 201-211) and index."]
[null,null,"Nota di contenuto",null,"Cover; Half-title; Title; Copyright; Dedication; Contents; Figures; Tables; Preface; CHAPTER 1 Event History and Social Science; CHAPTER 2 The Logic of Event History Analysis; CHAPTER 3 Parametric Models for Single-Spell Duration Data; CHAPTER 4 The Cox Proportional Hazards Model; CHAPTER 5 Models for Discrete Data; CHAPTER 6 Issues in Model Selection; CHAPTER 7 Inclusion of Time-Varying Covariates; CHAPTER 8 Diagnostic Methods for the Event History Model; CHAPTER 9 Some Modeling Strategies for Unobserved Heterogeneity; CHAPTER 10 Models for Multiple Events"]
[{"$nulls":4},"CHAPTER 11 The Social Sciences and Event HistoryAppendix Software for Event History Analysis; References; Index"]
[null,null,null,"Sommario/riassunto","Event History Modeling, first published in 2004, provides an accessible guide to event history analysis for researchers and advanced students in the social sciences. The substantive focus of many social science research problems leads directly to the consideration of duration models, and many problems would be better analyzed by using these "]
[{"$nulls":4},"longitudinal methods to take into account not only whether the event happened, but when. The foundational principles of event history analysis are discussed and ample examples are estimated and interpreted using standard statistical packages, such as STATA and S-Plus. Critical innovations in diagnostics are discussed, including testing the proportional hazards assumption, identifying outliers, and assessing model fit. The treatment of complicated events includes coverage of unobserved heterogeneity, repeated events, and competing risks models. The authors point out common problems in the analysis of time-to-event data in the social sciences and make recommendations regarding the implementation of duration modeling methods."]