LEADER 01190nam0-2200349---450- 001 990009869500403321 005 20140617085623.0 010 $a978-88-7016-941-6 035 $a000986950 035 $aFED01000986950 035 $a(Aleph)000986950FED01 035 $a000986950 100 $a20140617d2012----km-y0itay50------ba 101 0 $aita 102 $aIT 105 $aa-------001yy 200 1 $aRattazzi e gli statisti alessandrini tra storia, politica e istituzioni$enuovi studi sul Risorgimento$fa cura di Francesco Ingravalle e Stefano Quirico$gprefazione di Corrado Malandrino 210 $aTorino$cClaudiana$d2012 215 $a442 p.$c[4] c. di tav. : ill.$d24 cm 225 1 $aBiblioteca universitaria Claudiana$v2 610 0 $aRattazzi, Urbano$aSaggi 676 $a945.0842$v22$zita 702 1$aIngravalle,$bFrancesco 702 1$aQuirico,$bStefano 702 1$aMalandrino,$bCorrado$f<1950- > 801 0$aIT$bUNINA$gREICAT$2UNIMARC 901 $aBK 912 $a990009869500403321 952 $aCollez. 2431 (2)$b51673$fFSPBC 959 $aFSPBC 996 $aRattazzi e gli statisti alessandrini tra storia, politica e istituzioni$9827497 997 $aUNINA LEADER 05400nam 22006614a 450 001 9910143713103321 005 20170809164709.0 010 $a1-280-27600-2 010 $a9786610276004 010 $a0-470-09441-9 010 $a0-470-09440-0 035 $a(CKB)1000000000356520 035 $a(EBL)232706 035 $a(OCoLC)475938819 035 $a(SSID)ssj0000134956 035 $a(PQKBManifestationID)11134125 035 $a(PQKBTitleCode)TC0000134956 035 $a(PQKBWorkID)10057687 035 $a(PQKB)10619173 035 $a(MiAaPQ)EBC232706 035 $a(EXLCZ)991000000000356520 100 $a20050310d2005 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aData analysis and visualization in genomics and proteomics$b[electronic resource] /$feditors, Francisco Azuaje and Joaqui?n Dopazo 210 $aHoboken, NJ $cJohn Wiley$dc2005 215 $a1 online resource (285 p.) 300 $aDescription based upon print version of record. 311 $a0-470-09439-7 320 $aIncludes bibliographical references and index. 327 $aData 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 327 $a3 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 327 $a4.2 Introduction to Text Mining and NLP4.3 Databases and Resources 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 327 $aReferences6 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 327 $a7.4 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 327 $a8.3 Large-Scale High-Throughput Yeast Two-Hybrid Screens to Map the C. elegans Protein-Protein Interaction (Interactome) Network: Technical Aspects 330 $aData 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 606 $aGenomics$xData processing 606 $aProteomics$xData processing 606 $aData mining 608 $aElectronic books. 615 0$aGenomics$xData processing. 615 0$aProteomics$xData processing. 615 0$aData mining. 676 $a372.860285 676 $a572.8/6 701 $aAzuaje$b Francisco$0314953 701 $aDopazo$b Joaqui?n$0856093 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910143713103321 996 $aData analysis and visualization in genomics and proteomics$91911304 997 $aUNINA