Bioinformatics for Systems Biology

  • Stephen Krawetz

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Life of a Cell and Its Analysis

    1. Front Matter
      Pages 1-1
    2. Nadine Wiper-Bergeron, Ilona S. Skerjanc
      Pages 33-49
    3. Christina Karamboulas, Nadine Wiper-Bergeron, Ilona S. Skerjanc
      Pages 51-66
    4. Linda B. Bloom
      Pages 67-87
    5. Daniel A. Rappolee, D. Randall Armant
      Pages 89-104
    6. Sophie Rousseaux, Myriam Ferro
      Pages 105-117
  3. Statistical Tools and Their Application

    1. Front Matter
      Pages 137-137
    2. Michael L. Kruger
      Pages 139-150
    3. Gautam B. Singh
      Pages 151-162
    4. Jill S. Barnholtz-Sloan, Hemant K. Tiwari
      Pages 163-180
  4. Transcriptome Analysis

    1. Front Matter
      Pages 207-207
    2. Adrian E. Platts, Stephen A. Krawetz
      Pages 227-265
    3. Jingyi Hui, Shivendra Kishore, Amit Khanna, Stefan Stamm
      Pages 267-279
  5. Structural and Functional Sequence Analysis

  6. Literature Mining for Association and Meaning

    1. Front Matter
      Pages 367-367
    2. Heiko Dietze, Dimitra Alexopoulou, Michael R. Alvers, Liliana Barrio-Alvers, Bill Andreopoulos, Andreas Doms et al.
      Pages 385-399
    3. Florian Leitner, Robert Hoffmann, Alfonso Valencia
      Pages 413-433
  7. Genomic Databases

    1. Front Matter
      Pages 435-435
    2. Kiyoko F. Aoki-Kinoshita, Minoru Kanehisa
      Pages 437-452
    3. Anne Parker, Fiona Cunningham
      Pages 453-467
    4. Jeffrey H. Christiansen, Duncan R. Davidson, Richard A Baldock
      Pages 469-484
  8. Biological Networks

    1. Front Matter
      Pages 515-515
    2. Maria Manioudaki, Eleftheria Tzamali, Martin Reczko, Panayiota Poirazi
      Pages 517-539
    3. Eleftheria Tzamali, Panayiota Poirazi, Martin Reczko
      Pages 541-561
    4. Sachiyo Aburatani, Shigeru Saito, Katsuhisa Horimoto
      Pages 563-577
  9. Bridging the Gap

    1. Front Matter
      Pages 579-579
    2. David S. Wishart
      Pages 581-599
    3. Andrei L. Turinsky, Christoph W. Sensen
      Pages 601-613
    4. Craig Paul Webb, David Michael Cherba
      Pages 615-630
  10. Back Matter
    Pages 631-639

About this book


The biological sciences are now in the midst of a true life sciences revolution akin to what physics experienced just after the turn of the last century. We are now in a phase of unparalleled growth that is reflected by the amount of data generated from each experiment. At the time of this writing, the rate of data acquisition was approaching 2 terabytes over the course of 5 days with first pass analysis proceeding over the following 2-3 week period. This fundamental shift has provided unprecedented opportunities that for the first time afford us the ability, i.e., means, breadth, and depth of data, to truly address human biology at the systems level. This wealth of information from seemingly disparate datasets and its integration is being realized through bioinformatics. It is with this philosophy that the text Bioinformatics for Systems Biology was born. This revolution has spawned true personalized medicine that encompasses diagnostics and treatment through to cure.

For the physical and computer scientist, this text provides an introduction to the basic biological principles governing a cell. This quickly moves from the fundamentals to exploring the underlying genetic processes. While providing a rudimentary and necessary overview for the life scientist, the physical and computer scientist will be apprised of various nuances within the field reflecting the reality of "wet-bench" science. For those in the life sciences, it I rapidly becoming appreciated that we now progressing from examining our favorite "pet" gene to the system. Statistics is now an essential component to understand the vast datasets and this is emphasized throughout the text.

The majority of the text is devoted to the common ground that these groups share. It provides rich examples of tools, databases, and strategies to mine the databases to reveal novel insights. A host of examples of parsing the data into a series of overlays that use various presentation systems are reviewed. The goal is to provide a representation most comfortable to the user to enable the user to thoroughly explore the data. The text concludes with examples of how the systems information is used to inform personalized medicine in a true "bench to bedside" manner.

Bioinformatics for Systems Biology bridges and unifies many disciplines. It presents the life scientist, computational biologist, and mathematician with a common framework. Only by linking the groups together may the true life sciences revolution move forward in the mostly uncharted and emerging field of Systems Biology.


Ensembl Gap GoPubMed In silico Microarray T-Coffee bioinformatics biology databases genetics genome life sciences productionJC sequence analysis

Editors and affiliations

  • Stephen Krawetz
    • 1
  1. 1.Wayne State UniversityDetroitUSA

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