© 2012

Systems Biology in Cancer Research and Drug Discovery

  • Asfar S. Azmi

Table of contents

  1. Front Matter
    Pages i-xii
  2. Systems Biology in Cancer

    1. Front Matter
      Pages 1-1
    2. Mariano Bizzarri, Simona Dinicola, Cesare Manetti
      Pages 3-37
    3. Emanuela Gadaleta, Rosalind J. Cutts, Ajanthah Sangaralingam, Nicholas R. Lemoine, Claude Chelala
      Pages 83-111
    4. Zong-Xiu Wang, Rui-Ping Deng, Shu-Juan Guo, Ji-Bin Zhang, Sheng-Ce Tao
      Pages 113-134
  3. Systems Approaches to Understand Cancer Progression

    1. Front Matter
      Pages 165-165
    2. Emre Guney, Rebeca Sanz-Pamplona, Angels Sierra, Baldo Oliva
      Pages 167-195
    3. M. M. Quinas-Guerra, T. M. Ribeiro-Rodrigues, Juan Carlos Rodríguez-Manzaneque, Rui D. M. Travasso
      Pages 197-227
    4. Corban G. Rivera, Liang-Hui Chu, Joel S. Bader, Aleksander S. Popel
      Pages 229-244
  4. Systems and Network Biology in Decoding miRNA Complexity

  5. Network Modeling in Cancer Drug Discovery and Clinical Trials

    1. Front Matter
      Pages 307-307
    2. Mariaelena Pierobon, Julie Wulfkuhle, Lance A. Liotta, Emanuel F. Petricoin III
      Pages 309-323
    3. Aritro Nath, Christina Chan
      Pages 339-362

About this book


Systems Biology in Cancer Research and Drug Discovery provides a unique collection of chapters, by world-class researchers, describing the use of integrated systems biology and network modeling in the cancer field where traditional tools have failed to deliver expected promise. This book touches four applications/aspects of systems biology (i) in understanding aberrant signaling in cancer (ii) in identifying biomarkers and prognostic markers especially focused on angiogenesis pathways (iii) in unwinding microRNAs complexity and (iv) in anticancer drug discovery and in clinical trial design. This book reviews the state-of-the-art knowledge and touches upon cutting edge newer and improved applications especially in the area of network modeling. It is aimed at an audience ranging from students, academics, basic researcher and clinicians in cancer research. This book is expected to benefit the field of translational cancer medicine by bridging the gap between basic researchers, computational biologists and clinicians who have one ultimate goal and that is to defeat cancer.


Anti-Cancer Drug Discovery Bioinformatics Cancer Network Modelling Systems Biology

Editors and affiliations

  • Asfar S. Azmi
    • 1
  1. 1.Karmanos Cancer InstituteWayne State UniversityDetroitUSA

Bibliographic information

Industry Sectors
Health & Hospitals
Consumer Packaged Goods