Search

This book shows how to develop efficient quantitative methods to characterize neural data and extra information that reveals underlying dynamics and neurophysiological mechanisms. Written by active experts in the field, it contains an exchange of innovative ideas among researchers at both computational and experimental ends, as well as those at the interface. Authors discuss research challenges and new directions in emerging areas with two goals in mind: to collect recent advances in statistics, signal processing, modeling, and control methods in neuroscience; and to welcome and foster innovative or cross-disciplinary ideas along this line of research and discuss important research issues in neural data analysis. Making use of both tutorial and review materials, this book is written for neural, electrical, and biomedical engineers; computational neuroscientists; statisticians; computer scientists; and clinical engineers.

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.

Facilitating Interdisciplinary Research examines current interdisciplinary research efforts and recommends ways to stimulate and support such research. Advances in science and engineering increasingly require the collaboration of scholars from various fields. This shift is driven by the need to address complex problems that cut across traditional disciplines, and the capacity of new technologies to both transform existing disciplines and generate new ones. At the same time, however, interdisciplinary research can be impeded by policies on hiring, promotion, tenure, proposal review, and resource allocation that favor traditional disciplines. This report identifies steps that researchers, teachers, students, institutions, funding organizations, and disciplinary societies can take to more effectively conduct, facilitate, and evaluate interdisciplinary research programs and projects. Throughout the report key concepts are illustrated with case studies and results of the committee's surveys of individual researchers and university provosts.