{"product_id":"cancer-bioinformatics-isbn-9780470863046","title":"Cancer Bioinformatics","description":"\"The development and application of bioinformatics tools to basic and translational cancer research is, in fact, a rapidly expanding field that deserves a timely review. Therefore, a publication of this type is needed. The editors have done an excellent job in recruiting well-established scientists to author the various chapters of the book.\"\u003cbr\u003e —\u003cb\u003eDieter Naf\u003c\/b\u003e, Jackson Laboratory, USA  \u003cp\u003eCancer bioinformatics is now emerging as a new interdisciplinary field, which is facilitating an unprecedented synthesis of knowledge arising from the life and clinical sciences.\u003c\/p\u003e \u003cp\u003eThis groundbreaking title provides a comprehensive and up-to-date account of the enormous range of bioinformatics for cancer therapy development from the laboratory to clinical trials. It functions as a guide to integrated data exploitation and synergistic knowledge discovery, and support the consolidation of the interdisciplinary research community involved.\u003c\/p\u003e  \u003cb\u003ePreface.\u003c\/b\u003e  \u003cp\u003e\u003cb\u003eList of Contributors.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSECTION I CANCER SYSTEMS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 A Path to Knowledge: from Data to Complex Systems Models of Cancer\u003c\/b\u003e (\u003ci\u003eSylvia Nagl\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e1.1 Conceptual foundations: biological complexity.\u003c\/p\u003e \u003cp\u003e1.2 A taxonomy of cancer complexity.\u003c\/p\u003e \u003cp\u003e1.3 Modelling and simulation of cancer systems.\u003c\/p\u003e \u003cp\u003e1.4 Data standards and integration.\u003c\/p\u003e \u003cp\u003e1.5 Concluding remarks.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Theory of Cancer Robustness\u003c\/b\u003e (\u003ci\u003eHiroaki Kitano\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e2.1 Robustness: the fundamental organizational principle of biological systems.\u003c\/p\u003e \u003cp\u003e2.2 Underlying mechanisms for robustness.\u003c\/p\u003e \u003cp\u003e2.3 Intrinsic features of robust systems: evolvability and trade-offs.\u003c\/p\u003e \u003cp\u003e2.4 Cancer as a robust system.\u003c\/p\u003e \u003cp\u003e2.5 Therapy strategies.\u003c\/p\u003e \u003cp\u003e2.6 A proper index of treatment efficacy.\u003c\/p\u003e \u003cp\u003e2.7 Computational tools.\u003c\/p\u003e \u003cp\u003e2.8 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Developing an Integrated Informatics Platform for Cancer Research\u003c\/b\u003e (\u003ci\u003eRichard Begent\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e3.1 Background.\u003c\/p\u003e \u003cp\u003e3.2 The challenge.\u003c\/p\u003e \u003cp\u003e3.3 The UK National Cancer Research Institute (NCRI) informatics platform.\u003c\/p\u003e \u003cp\u003e3.4 Developing the informatics platform.\u003c\/p\u003e \u003cp\u003e3.5 Benefits of the platform.\u003c\/p\u003e \u003cp\u003e3.6 Conclusions.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSECTION II\u003c\/b\u003e \u003ci\u003e\u003cb\u003eIn silico\u003c\/b\u003e\u003c\/i\u003e \u003cb\u003eMODELS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Mathematical Models of Cancer\u003c\/b\u003e (\u003ci\u003eManish Patel\u003c\/i\u003e and \u003ci\u003eSylvia Nagl\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e4.1 Growth models.\u003c\/p\u003e \u003cp\u003e4.2 A very brief tour of cellular automata.\u003c\/p\u003e \u003cp\u003e4.3 Angiogenesis models.\u003c\/p\u003e \u003cp\u003e4.4 Treatment response models.\u003c\/p\u003e \u003cp\u003e4.5 Dynamic pathways models.\u003c\/p\u003e \u003cp\u003e4.6 Other models.\u003c\/p\u003e \u003cp\u003e4.7 Simulations of complex biological systems.\u003c\/p\u003e \u003cp\u003e4.8 Concluding remarks.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Some Mathematical Modelling Challenges and Approaches in Cancer\u003c\/b\u003e (\u003ci\u003ePhilip Maini\u003c\/i\u003e and \u003ci\u003eRobert A. Gatenby\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e5.1 Introduction.\u003c\/p\u003e \u003cp\u003e5.2 Multiscale modelling.\u003c\/p\u003e \u003cp\u003e5.3 Tumour vascular modelling.\u003c\/p\u003e \u003cp\u003e5.4 Population models.\u003c\/p\u003e \u003cp\u003e5.5 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Computer Simulation of Tumour Response to Therapy\u003c\/b\u003e (\u003ci\u003eGeorgios S. Stamatakos\u003c\/i\u003e and \u003ci\u003eNikolaos Uzunoglu\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e6.1 Introduction.\u003c\/p\u003e \u003cp\u003e6.2 Tumour growth simulation.\u003c\/p\u003e \u003cp\u003e6.3 Radiotherapy response simulation.\u003c\/p\u003e \u003cp\u003e6.4 Chemotherapy response simulation.\u003c\/p\u003e \u003cp\u003e6.5 Simulation of tumour response to other therapeutic modalities.\u003c\/p\u003e \u003cp\u003e6.6 Simulation of normal tissue response to antineoplastic interventions.\u003c\/p\u003e \u003cp\u003e6.7 Integration of molecular networks into tumour behaviour simulations.\u003c\/p\u003e \u003cp\u003e6.8 Future directions.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Structural Bioinformatics in Cancer\u003c\/b\u003e (\u003ci\u003eStephen Neidle\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e7.1 Introduction.\u003c\/p\u003e \u003cp\u003e7.2 Macromolecular crystallography.\u003c\/p\u003e \u003cp\u003e7.3 Molecular modelling.\u003c\/p\u003e \u003cp\u003e7.4 Conclusions.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSECTION III\u003c\/b\u003e \u003ci\u003e\u003cb\u003eIn vivo\u003c\/b\u003e\u003c\/i\u003e \u003cb\u003eMODELS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 The Mouse Tumour Biology Database: an Online Resource for Mouse Models of Human Cancer\u003c\/b\u003e (\u003ci\u003eCarol J. Bult, Debra M. Krupke, Matthew J. Vincent, Theresa Allio, John P. Sundberg, Igor Mikaelian\u003c\/i\u003e and \u003ci\u003eJanan T. Eppig\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e8.1 Introduction.\u003c\/p\u003e \u003cp\u003e8.2 Background.\u003c\/p\u003e \u003cp\u003e8.3 Database content.\u003c\/p\u003e \u003cp\u003e8.4 Data acquisition.\u003c\/p\u003e \u003cp\u003e8.5 Using the MTB database.\u003c\/p\u003e \u003cp\u003e8.6 Connecting the MTB database with related databases.\u003c\/p\u003e \u003cp\u003e8.7 Summary.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Bioinformatics Approaches to Integrate Cancer Models and Human Cancer Research\u003c\/b\u003e (\u003ci\u003eCheryl L. Marks\u003c\/i\u003e and \u003ci\u003eSue Dubman\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e9.1 Background.\u003c\/p\u003e \u003cp\u003e9.2 The MMHCC Informatics at the outset of the programme.\u003c\/p\u003e \u003cp\u003e9.3 Initial NCI bioinformatics infrastructure development.\u003c\/p\u003e \u003cp\u003e9.4 Future directions for informatics support.\u003c\/p\u003e \u003cp\u003e9.5 Summary.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSECTION IV DATA.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 The FAPESP\/LICR Human Cancer Genome Project: Perspectives on Integration\u003c\/b\u003e (\u003ci\u003eRicardo Brentani, Anamaria A. Camargo, Helena Brentani\u003c\/i\u003e and \u003ci\u003eSandro J. De Souza\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e10.1 Introduction.\u003c\/p\u003e \u003cp\u003e10.2 The FAPESP\/LICR Human Cancer Genome Project.\u003c\/p\u003e \u003cp\u003e10.3 An integrated view of the tumour transcriptome.\u003c\/p\u003e \u003cp\u003e10.4 Summary.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Today’s Science, Tomorrow’s Patient: the Pivotal Role of Tissue, Clinical Data and Informatics in Modern Drug Development\u003c\/b\u003e (\u003ci\u003eKirstine Knox, Amanda Taylor\u003c\/i\u003e and \u003ci\u003eDavid J. Kerr\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e11.1 Introduction.\u003c\/p\u003e \u003cp\u003e11.2 A new national strategy for the provision of tissue annotated with clinical information to meet current and future needs of academic researchers and industry.\u003c\/p\u003e \u003cp\u003e11.3 The NCRI National Cancer Tissue Resource for cancer biology and treatment development.\u003c\/p\u003e \u003cp\u003e11.4 A potential future world-class resource integrating research and health service information systems and bioinformatics for cancer diagnosis and treatment.\u003c\/p\u003e \u003cp\u003e11.5 A proposed information system architecture that will meet the challenges and deliver the required functionality: an overview.\u003c\/p\u003e \u003cp\u003e11.6 Consent and confidentiality: ensuring that the NCTR is embedded in the UK’s legal and ethical framework.\u003c\/p\u003e \u003cp\u003e11.7 Concluding remarks: future challenges and opportunities.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSECTION V ETHICS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Software Design Ethics for Biomedicine\u003c\/b\u003e (\u003ci\u003eDon Gotterbarn\u003c\/i\u003e and \u003ci\u003eSimon Rogerson\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e12.1 The problem: software and research.\u003c\/p\u003e \u003cp\u003e12.2 Risk identification.\u003c\/p\u003e \u003cp\u003e12.3 Biomedical software example.\u003c\/p\u003e \u003cp\u003e12.4 Is an ethical risk analysis required?\u003c\/p\u003e \u003cp\u003e12.5 Details of SoDIS.\u003c\/p\u003e \u003cp\u003e12.6 A SoDIS analysis of the biomedical software example.\u003c\/p\u003e \u003cp\u003e12.7 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Ethical Issues of Electronic Patient Data and Informatics in Clinical Trial Settings\u003c\/b\u003e (\u003ci\u003eDipak Kalra\u003c\/i\u003e and \u003ci\u003eDavid Ingram\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e13.1 Introduction.\u003c\/p\u003e \u003cp\u003e13.2 Ethical aspects of using patient-identifiable health data.\u003c\/p\u003e \u003cp\u003e13.3 Legislation and policies pertaining to patient-identifiable health data.\u003c\/p\u003e \u003cp\u003e13.4 Using anonymized and pseudonymized data.\u003c\/p\u003e \u003cp\u003e13.5 Protecting personal health data.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Pharmacogenomics and Cancer: Ethical, Legal and Social Issues\u003c\/b\u003e (\u003ci\u003eMary Anderlik Majumder\u003c\/i\u003e and \u003ci\u003eMark Rothstein\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e14.1 Introduction.\u003c\/p\u003e \u003cp\u003e14.2 Getting pharmacogenomic tests and drugs to market.\u003c\/p\u003e \u003cp\u003e14.3 Cost and coverage issues.\u003c\/p\u003e \u003cp\u003e14.4 Ethical challenges of pharmacogenomics.\u003c\/p\u003e \u003cp\u003e14.5 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIndex\u003c\/b\u003e\u003c\/p\u003e  \"…recommended for purchase for medical, academic or special libraries serving basic or clinical cancer researchers and bioinformaticists.\" (\u003ci\u003eE-STREAMS\u003c\/i\u003e, September 2007)  \u003cp\u003e\"…good reading for anyone entering into some aspect of cancer research, whether it is biological, mathematical, or computational…\" (\u003ci\u003eBiometrics\u003c\/i\u003e, December 2006)\u003c\/p\u003e \u003cp\u003e\"Overall … an excellent and well-edited book that could be read from cover to cover or used as a reference.\" (\u003ci\u003eBritish Journal of Healthcare Computing and Information Management\u003c\/i\u003e, July 2006)\u003c\/p\u003e Dr Sylvia Nagl, Senior Lecturer, Department of Oncology, University College, London  The emerging field of cancer bioinformatics is facilitating an unprecedented synthesis of knowledge arising from the life and clinical sciences. The complexity of the questions being addressed requires experts from diverse backgrounds to engage in close and ongoing discourse and collaboration. They therefore need to be familiar with the research questions, terminology and methodology of the specialists in related subject areas.  \u003cp\u003eThe primary aim of the book is to provide a comprehensive and up-to-date account of the enormous range of bioinformatics techniques now being developed for cancer research and therapy, from the laboratory to clinical trials. It will function as a guide to integrated data exploitation and synergistic knowledge discovery, and support the consolidation of the multidisciplinary research community involved.\u003c\/p\u003e \u003cp\u003eThe book features a balanced range of topics, including both well-established techniques and emergent approaches in genomics, systems biology and e-science. Each chapter delivers an overview of the topic, combined with more detailed technical descriptions of key aspects of informatics, biology and clinical science. With contributions from clinical oncologists, research scientists, bioinformaticians and mathematical modellers, the book will facilitate scientific dialogue and collaboration across disciplinary boundaries. Finally, three chapters on the ethical and legal implications of cancer bioinformatics provide an expanded view of these groundbreaking developments and how they may impact on patients and other health care stakeholders.\u003c\/p\u003e \u003cp\u003eThis multidisciplinary book will be of interest to a broad audience including clinical oncologists, basic researchers in both academia and industry, computer scientists\/bioinformaticians, clinical trial managers, ethicists and ethics boards.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988880703717,"sku":"NP9780470863046","price":164.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780470863046.jpg?v=1761781897","url":"https:\/\/k12savings.com\/products\/cancer-bioinformatics-isbn-9780470863046","provider":"K12savings","version":"1.0","type":"link"}