Multi-modal representations, the lack of complete and consistent domain theories, rapid evolution of domain knowledge, high dimensionality, and large amounts of missing information - these are challenges inherent in modern proteomics. As our understanding of protein structure and function becomes ever more complicated, we have reached a point where the actual management of data is a major stumbling block to the interpretation of results from proteomic platforms, to knowledge discovery. "Knowledge Discovery in Proteomics" presents timely, authoritative discussions on some of the key issues in high-throughput proteomics, exploring examples that represent some of the major challenges of knowledge discovery in the field. The authors focus on five specific domains: Mass spectrometry-based protein analysis; Protein-protein interaction network analysis; Systematic high-throughput protein crystallization; Systematic, integrated analysis of multiple data repositories; and Systems biology In each area. The authors describe the challenges created by the type of data produced and present potential solutions to the problem of data mining within the domain. They take a systems approach, covering individual data and integrating its computational aspects, from data preprocessing, storage, and access to analysis, visualization, and interpretation. With clear exposition, practical examples, and rich illustrations, this book presents an outstanding overview of this emerging field, and builds the background needed for the fruitful exchange of ideas between computational and biological scientists.
INTRODUCTIONKnowledge DiscoveryProteomicsKNOWLEDGE MANAGEMENTComputational Analysis, Visualization, and Interpretation of HTP Proteomic DataIntroduction to Data ManagementKnowledge ManagementConclusionsCURRENT STATUS AND FUTURE PROSPECTS OF MASS SPECTROMETRYBasic Concepts of Mass SpectrometryMultidimensional ChromatographyProtein QuantitationDetection of Post-Translation ModificationsGlobal Data Analysis, Informatics Resources, and Data MiningGRAPH THEORY ANALYSIS OF PROTEIN-PROTEIN INTERACTIONSGraph Theoretic TerminologyBiological TerminologyLarge Network ModelsProtein Interaction NetworksDetection of Dense SubnetworksConclusionsHTP PROTEIN CRYSTALLIZATION APPROACHESProtein CrystallizationImage Analysis in http Protein CrystallizationCase-based Planning of Crystallization ExperimentsProtein Crystallization Knowledge DiscoveryConclusionsINTEGRATION OF DIVERSE DATA, ALGORITHMS, AND DOMAINSIntegration of Data and ToolsCharacterizing and Predicting Protein-Protein InteractionsApproaches to Data IntegrationConclusionsFROM HIGH-THROUGHPUT TO SYSTEMS BIOLOGYAn Overview of Systems BiologySystematic BiologyProtein-Protein InteractionsModular Biology from Protein Interaction DomainsProtein Interaction NetworksTheoretical Models of Biological SystemsSoftware Development for System ModelingCancer as a System FailureReferences