Biology 2e is designed to cover the scope and sequence requirements of a typical two-semester biology course for science majors. The text provides comprehensive coverage of foundational research and core biology concepts through an evolutionary lens. Biology includes rich features that engage students in scientific inquiry, highlight careers in the biological sciences, and offer everyday applications. The book also includes various types of practice and homework questions that help students understand—and apply—key concepts. The 2nd edition has been revised to incorporate clearer, more current, and more dynamic explanations, while maintaining the same organization as the first edition. Art and illustrations have been substantially improved, and the textbook features additional assessments and related resources.
By the end of this section, you will be able to do the following:
Define population genetics and describe how scientists use population genetics in studying population evolution
Define the Hardy-Weinberg principle and discuss its importance
An integrated course stressing the principles of biology. Life processes are examined primarily at the organismal and population levels. Intended for students majoring in biology or for non-majors who wish to take advanced biology courses.
This course presents a unique and challenging perspective on the causes of human disease and mortality. The course focuses on analyses of major causes of mortality in the US since 1900: cancer cardiovascular and cerebrovascular diseases, diabetes, infectious diseases. Students create analytical models to derive estimates for historically variant population risk factors and physiological rate parameters, and conduct analyses of familial data to separately estimate inherited and environmental risks. The course evaluates the basic population genetics of dominant, recessive and non-deleterious inherited risk factors.
Subject assesses the relationships between sequence, structure, and function in complex biological networks as well as progress in realistic modeling of quantitative, comprehensive functional-genomics analyses. Topics include: algorithmic, statistical, database, and simulation approaches; and practical applications to biotechnology, drug discovery, and genetic engineering. Future opportunities and current limitations critically assessed. Problem sets and project emphasize creative, hands-on analyses using these concepts.