Data Mining in Biomedicine (eBook)
XVII, 582 Seiten
Springer US (Verlag)
978-0-387-69319-4 (ISBN)
This volume presents an extensive collection of contributions covering aspects of the exciting and important research field of data mining techniques in biomedicine. Coverage includes new approaches for the analysis of biomedical data; applications of data mining techniques to real-life problems in medical practice; comprehensive reviews of recent trends in the field. The book addresses incorporation of data mining in fundamental areas of biomedical research: genomics, proteomics, protein characterization, and neuroscience.
This volume presents an extensive collection of contributions covering aspects of the exciting and important research field of data mining techniques in biomedicine. Coverage includes new approaches for the analysis of biomedical data; applications of data mining techniques to real-life problems in medical practice; comprehensive reviews of recent trends in the field. The book addresses incorporation of data mining in fundamental areas of biomedical research: genomics, proteomics, protein characterization, and neuroscience.
Contents 6
Preface 10
List of Contributors 12
Recent Methodological Developments for Data Mining Problems in Biomedicine 19
Pattern- Based Discriminants in the Logical Analysis of Data 20
Exploring Microarray Data with Correspondence Analysis 41
An Ensemble Method of Discovering Sample Classes Using Gene Expression Profiling 54
CpG Island Identification with Higher Order and Variable Order Markov Models 62
Data Mining Algorithms for Virtual Screening of Bioactive Compounds 73
Sparse Component Analysis: a New Tool for Data Mining 105
Data Mining Via Entropy and Graph Clustering 131
Molecular Biology and Pooling Design 146
An Optimization Approach to Identify the Relationship between Features and Output of a Multi- label Classifier 153
Classifying Noisy and Incomplete Medical Data by a Differential Latent Semantic Indexing Approach 180
Ontology Search and Text Mining of MEDLINE Database 188
Data Mining Techniques in Disease Diagnosis 201
Logical Analysis of Computed Tomography Data to Differentiate Entities of Idiopathic Interstitial Pneumonias 202
Diagnosis of Alport Syndrome by Pattern Recognition Techniques 218
Clinical Analysis of the Diagnostic Classification of Geriatric Disorders 240
Data Mining Studies in Genomics and Proteomics 268
A Hybrid Knowledge Based- Clustering Multi- Class SVM Approach for Genes Expression Analysis 270
Mathematical Programming Formulations for Problems in Genomics and Proteomics 284
Inferring the Origin of the Genetic Code 300
Deciphering the Structures of Genomic DNA Sequences Using Recurrence Time Statistics 330
Clustering Proteomics Data Using Bayesian Principal Component Analysis 347
Bioinformatics for Traumatic Brain Injury: Proteomic Data Mining 371
Capillary LC separation of tryptic peptides 385
Characterization and Prediction of Protein Structure 396
Computational Methods for Protein Fold Prediction: an Ab- initio Topological Approach 397
A Topological Characterization of Protein Structure 436
Applications of Data Mining Techniques to Brain Dynamics Studies 461
Data Mining in EEG: Application to Epileptic Brain Disorders* 462
Information Flow in Coupled Nonlinear Systems: Application to the Epileptic Human Brain 485
Reconstruction of Epileptic Brain Dynamics Using Data Mining Techniques 506
Automated Seizure Prediction Algorithm and its Statistical Assessment: A Report from Ten Patients* 517
Seizure Predictability in an Experimental Model of Epilepsy* 534
Network- Based Techniques in EEG Data Analysis and Epileptic Brain Modeling 558
Index 573
| Erscheint lt. Verlag | 10.12.2008 |
|---|---|
| Reihe/Serie | Springer Optimization and Its Applications | Springer Optimization and Its Applications |
| Zusatzinfo | XVIII, 580 p. |
| Verlagsort | New York |
| Sprache | englisch |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Medizin / Pharmazie ► Allgemeines / Lexika | |
| Medizin / Pharmazie ► Medizinische Fachgebiete ► Biomedizin | |
| Medizin / Pharmazie ► Physiotherapie / Ergotherapie ► Orthopädie | |
| Studium ► 1. Studienabschnitt (Vorklinik) ► Biochemie / Molekularbiologie | |
| Technik ► Bauwesen | |
| Technik ► Medizintechnik | |
| Wirtschaft ► Betriebswirtschaft / Management ► Planung / Organisation | |
| Schlagworte | algorithms • Bioinformatics • biomedicine • classification • Clustering • Computed tomography (CT) • Data Analysis • Data Mining • Dynamics • linear optimization • Optimization • Statistica • Statistics |
| ISBN-10 | 0-387-69319-X / 038769319X |
| ISBN-13 | 978-0-387-69319-4 / 9780387693194 |
| Haben Sie eine Frage zum Produkt? |
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