Computational Medicine

Tools and Challenges

  • Zlatko Trajanoski

Table of contents

  1. Front Matter
    Pages i-ix
  2. Stefan Coassin, Anita Kloss-Brandstätter, Florian Kronenberg
    Pages 1-25
  3. Lukas Forer, Sebastian Schönherr, Hansi Weißensteiner, Günther Specht, Florian Kronenberg, Anita Kloss-Brandstätter
    Pages 27-36
  4. Bettina Halwachs, Gregor Gorkiewicz, Gerhard G. Thallinger
    Pages 37-57
  5. Julia Feichtinger, Gerhard G. Thallinger, Ramsay J. McFarlane, Lee D. Larcombe
    Pages 59-77
  6. Florian Paul Breitwieser, Jacques Colinge
    Pages 79-91
  7. Jürgen Hartler, Harald C. Köfeler, Christopher J. O. Baker, Ravi Tharakan, Gerhard G. Thallinger
    Pages 93-109
  8. Georg Schneider, Westley Sherman, Durga Kuchibhatla, Hong Sain Ooi, Fernanda L. Sirota, Sebastian Maurer-Stroh et al.
    Pages 111-143
  9. Kristina Djinović-Carugo, Oliviero Carugo
    Pages 145-158
  10. Pornpimol Charoentong, Hubert Hackl, Bernhard Mlecnik, Gabriela Bindea, Jerome Galon, Zlatko Trajanoski
    Pages 159-172
  11. M. Osl, M. Netzer, S. Dreiseitl, C. Baumgartner
    Pages 173-184
  12. Laurin A. J. Mueller, Matthias Dehmer, Frank Emmert-Streib
    Pages 185-197
  13. Back Matter
    Pages 199-203

About this book


Computational methodologies and modeling play a growing role for investigating mechanisms, and for the diagnosis and therapy of human diseases. This progress gave rise to computational medicine, an interdisciplinary field at the interface of computer science and medicine. The main focus of computational medicine lies in the development of data analysis methods and mathematical modeling as well as computational simulation techniques specifically addressing medical problems. In this book, we present a number of computational medicine topics at several scales: from molecules to cells, organs, and organisms. At the molecular level, tools for the analysis of genome variations as well as cloud computing resources for medical genetics are reviewed. Then, an analysis of gene expression data and the application to the characterization of microbial communities are highlighted. At the protein level, two types of analyses for mass spectrometry data are reviewed: labeled quantitative proteomics and lipidomics, followed by protein sequence analysis and a 3D structure and drug design chapter. Finally, three chapters on clinical applications focus on the integration of biomolecular and clinical data for cancer research, biomarker discovery, and network-based methods for computational diagnostics.


computational medicine

Editors and affiliations

  • Zlatko Trajanoski
    • 1
  1. 1., Section for BioinformaticsMedical University of InnsbruckInnsbruckAustria

Bibliographic information