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  • Book
  • © 2012

Data Mining for Biomarker Discovery

  • Presents the most challenging problems in biomarker discovery together with the most prominent methodological approaches for developing their effective solution
  • Offers the collaborative perspectives of distinguished researchers in the fields of biomedicine, biochemistry, data mining and machine learning
  • Introduces new spectral clustering, and hierarchical clustering algorithms specifically crafted for use in a large bioinformatics database

Part of the book series: Springer Optimization and Its Applications (SOIA, volume 65)

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xiv
  2. Data Mining Strategies Applied in Brain Injury Models

    • Stefania Mondello, Firas Kobeissy, Isaac Fingers, Zhiqun Zhang, Ronald L. Hayes, Kevin K. W. Wang
    Pages 1-13
  3. Application of Decomposition Methods in the Filtering of Event-Related Potentials

    • Kostas Michalopoulos, Vasiliki Iordanidou, Michalis Zervakis
    Pages 15-29
  4. EEG Features as Biomarkers for Discrimination of Preictal States

    • Alkiviadis Tsimpiris, Dimitris Kugiumtzis
    Pages 31-56
  5. Using Relative Power Asymmetry as a Biomarker for Classifying Psychogenic Nonepileptic Seizure and Complex Partial Seizure Patients

    • Jui-Hong Chien, Deng-Shan Shiau, J. Chris Sackellares, Jonathan J. Halford, Kevin M. Kelly, Panos M. Pardalos
    Pages 57-77
  6. Classification of Tree and Network Topology Structures in Medical Images

    • Angeliki Skoura, Vasileios Megalooikonomou, Athanasios Diamantopoulos, George C. Kagadis, Dimitrios Karnabatidis
    Pages 79-90
  7. A Framework for Multimodal Imaging Biomarker Extraction with Application to Brain MRI

    • Kostas Marias, Vangelis Sakkalis, Norbert Graf
    Pages 91-116
  8. A Statistical Diagnostic Decision Support Tool Using Magnetic Resonance Spectroscopy Data

    • Evaggelia Tsolaki, Evanthia Kousi, Eftychia Kapsalaki, Ioannis Dimou, Kyriaki Theodorou, Georgios C. Manikis et al.
    Pages 117-142
  9. Data Mining for Cancer Biomarkers with Raman Spectroscopy

    • Michael B. Fenn, Vijay Pappu
    Pages 143-168
  10. Nonlinear Recognition Methods for Oncological Pathologies

    • Gregorio Patrizi, Vincenzo Pietropaolo, Antonella Carbone, Renato De Leone, Laura Di Giacomo, Valentina Losacco et al.
    Pages 169-185
  11. Studying Connectivity Properties in Human Protein–Protein Interaction Network in Cancer Pathway

    • Vera Tomaino, Ashwin Arulselvan, Pierangelo Veltri, Panos M. Pardalos
    Pages 187-197
  12. Modelling of Oral Cancer Progression Using Dynamic Bayesian Networks

    • Konstantinos P. Exarchos, George Rigas, Yorgos Goletsis, Dimitrios I. Fotiadis
    Pages 199-212
  13. Neuromuscular Alterations of Upper Airway Muscles in Patients with OSAS: Radiological and Histopathological Findings

    • Panagis Drakatos, Dimosthenis Lykouras, Fotis Sampsonas, Kiriakos Karkoulias, Kostas Spiropoulos
    Pages 213-226
  14. Data Mining System Applied to Population Databases for Studies on Lung Cancer

    • J. Pérez, F. Henriques, R. Santaolaya, O. Fragoso, A. Mexicano
    Pages 227-246

About this book

Biomarker discovery is an important area of biomedical research that may lead to significant breakthroughs in disease analysis and targeted therapy. Biomarkers are biological entities whose alterations are measurable and are characteristic of a particular biological condition. Discovering, managing, and interpreting knowledge of new biomarkers are challenging and attractive problems in the emerging field of biomedical informatics.

This volume is a collection of state-of-the-art research into the application of data mining to the discovery and analysis of new biomarkers. Presenting new results, models and algorithms, the included contributions focus on biomarker data integration, information retrieval methods, and statistical machine learning techniques.

This volume is intended for students, and researchers in bioinformatics, proteomics, and genomics, as well engineers and applied scientists interested in the interdisciplinary application of data mining techniques.

Editors and Affiliations

  • , Department of Industrial & Systems Engin, University of Florida, Gainesville, USA

    Panos M. Pardalos, Petros Xanthopoulos

  • Dept. Electronic & Computer, Engineering, Technical University of Crete, Chania, Crete, Greece

    Michalis Zervakis

Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access