National Research Council; Division on Engineering and Physical Sciences; Board on Mathematical Sciences and Their Applications National Academies Press (2005) Pehmeäkantinen kirja
National Research Council; Board on Mathematical Sciences and Their Applications; Committee on Directions for the AFOSR Mathemat National Academies Press (2006) Pehmeäkantinen kirja
National Research Council; Division on Engineering and Physical Sciences; Board on Mathematical Sciences and Their Applications National Academies Press (2010) Pehmeäkantinen kirja
National Research Council; Division on Engineering and Physical Sciences; Board on Mathematical Sciences and Their Applications National Academies Press (2012) Pehmeäkantinen kirja
National Research Council; Division on Engineering and Physical Sciences; Board on Mathematical Sciences and Their Applications National Academies Press (2013) Pehmeäkantinen kirja
National Research Council; Division on Engineering and Physical Sciences; Board on Mathematical Sciences and Their Applications National Academies Press (2012) Pehmeäkantinen kirja
National Research Council; Division on Engineering and Physical Sciences; Board on Mathematical Sciences and Their Applications National Academies Press (2004) Pehmeäkantinen kirja
National Research Council; Board on Mathematical Sciences and Their Applications; Mathematical Sciences Education Board National Academies Press (1989) Pehmeäkantinen kirja
National Research Council; Division on Engineering and Physical Sciences; Board on Mathematical Sciences and Their Applications National Academies Press (2015) Pehmeäkantinen kirja
National Research Council; Division on Engineering and Physical Sciences; Board on Mathematical Sciences and Their Applications National Academies Press (2010) Pehmeäkantinen kirja
The exponentially increasing amounts of biological data along with comparable advances in computing power are making possible the construction of quantitative, predictive biological systems models. This development could revolutionize those biology-based fields of science. To assist this transformation, the U.S. Department of Energy asked the National Research Council to recommend mathematical research activities to enable more effective use of the large amounts of existing genomic information and the structural and functional genomic information being created. The resulting study is a broad, scientifically based view of the opportunities lying at the mathematical science and biology interface. The book provides a review of past successes, an examination of opportunities at the various levels of biological systems— from molecules to ecosystems—an analysis of cross-cutting themes, and a set of recommendations to advance the mathematics-biology connection that are applicable to all agencies funding research in this area.Table of Contents
Front Matter Executive Summary 1 The Nature of the Field 2 Historical Successes 3 Understanding Molecules 4 Understanding Cells 5 Understanding Organisms 6 Understanding Populations 7 Understanding Communities and Ecosystems 8 Crosscutting Themes