Systems Biology in Cancer Research and Drug Discovery [electronic resource] /
Azmi, Asfar S.editor.
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.
Description based upon print version of record.
""Systems Biology in Cancer Research and Drug Discovery ""; ""Preface""; ""Acknowledgment""; ""Contents""; ""Part I: Systems Biology in Cancer""; ""Chapter 1: Systems Biology Approach to Metabolomics in Cancer Studies""; ""1 Why Are Metabolomics Studies so Relevant for Cancer Studies?""; ""2 Metabolomic Fingerprint of Cancer""; ""2.1 High Glycolytic Fluxes""; ""2.2 Redox State""; ""2.3 De Novo Synthesis of Nucleic Acids""; ""2.4 Lipogenesis""; ""3 Metabolism and Cancer: Cause or Epiphenomenona?""; ""4 Is the Glycolytic Phenotype Really a Specific Hallmark of Cancer?""
""4.1 Embryo Metabolism""""4.2 Wound Healing""; ""5 Microenvironment Reversion of Cancer Metabolomic Fingerprint""; ""6 Complexity of Metabolism Regulation""; ""7 Metabolomic Studies Promote a Systems Biology View of Cancer""; ""8 Metabolomic Studies in a Systems Biology Perspective""; ""9 Conclusion""; ""References""; ""Chapter 2: System Biology Approach to Study Cancer Related Pathways""; ""1 Introduction""; ""2 Understanding the Role of p53 in Cancer""; ""2.1 Introduction of Cancer""; ""2.2 Roles of p53 in Cancer""; ""3 The p53 Pathway""; ""3.1 Input Signals""; ""3.2 Upstream Mediators""
""3.3 Core Regulation Components""""3.4 Downstream Targets""; ""3.5 Cellular Outputs""; ""4 The Study of MDM2-p53 Negative Feedback Loop""; ""4.1 Building the Mechanistic Model of Biological Pathway""; ""4.1.1 Basic Kinetic Description""; ""4.1.2 Formal Specification Methods""; ""4.1.3 Parameter Estimation Methods""; ""4.2 Mechanistic Model of p53 Pathway""; ""4.2.1 Introduction of Motif""; ""4.2.2 Negative Feedback Loop in p53 Core Component Pathway""; ""4.2.3 Methods to Choose Model""; ""5 Discussion of Crosstalk in p53 Pathway""; ""6 Conclusion""; ""References""
""Chapter 3: Modeling Oncogenic Signaling Networks from Gene Expression Dynamics""""1 Oncogenes, Tumor Suppressors and Targeted Cancer Therapies""; ""2 Transcriptional Network Modeling""; ""2.1 Advantages to Analyzing Perturbed Model Systems and Temporal Dynamics of Gene Expression""; ""2.2 Examples of Signaling Network Modeling Strategies and Outcomes""; ""3 Perspective on Discovering Druggable Targets and Increasing Network Complexity""; ""References""; ""Chapter 4: An Integrated Systems Approach to the Study of Pancreatic Cancer""; ""1 Introduction""; ""2 Pancreatic Cancer""
""2.1 From the â€?Omics Era to the Dawn of Genome Sequencing""""3 The Pancreatic Cancer International Cancer Genome Consortium Project""; ""3.1 The ICGC Data Portal""; ""3.2 BioMart""; ""4 Global Data Mining and Integration Approaches""; ""4.1 Single Data Types""; ""4.2 Multiple Data Types: Pancreatic Expression Database""; ""4.2.1 Detailed Analysis of Genes Involved in Pancreatic Cancer""; ""4.2.2 Cross-Querying with Other BioMart-Compliant Resources""; ""4.3 Challenges and Solutions""; ""References""; ""Chapter 5: Protein Microarray: An Ideal Platform for Systems Biology""
""1 Introduction""
Includes bibliographical references and index.
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.
Medicine.
Cancer research.
Systems biology.
Bioinformatics.
Biomedicine, general.
Cancer Research.
Systems Biology.
Bioinformatics.