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Biology
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Biology is designed for multi-semester biology courses for science majors. It is grounded on an evolutionary basis and includes exciting features that highlight careers in the biological sciences and everyday applications of the concepts at hand. To meet the needs of today’s instructors and students, some content has been strategically condensed while maintaining the overall scope and coverage of traditional texts for this course. Instructors can customize the book, adapting it to the approach that works best in their classroom. Biology also includes an innovative art program that incorporates critical thinking and clicker questions to help students understand—and apply—key concepts.

Subject:
Biology
Life Science
Material Type:
Full Course
Provider:
Rice University
Provider Set:
OpenStax College
Date Added:
08/12/2021
Biology, The Cell, Cell Structure, Eukaryotic Cells
Conditional Remix & Share Permitted
CC BY-NC
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By the end of this section, you will be able to:Describe the structure of eukaryotic cellsCompare animal cells with plant cellsState the role of the plasma membraneSummarize the functions of the major cell organelles

Subject:
Biology
Life Science
Material Type:
Module
Author:
OER Librarian
Date Added:
08/12/2021
Cell Biology: Structure and Functions of the Nucleus, Spring 2010
Conditional Remix & Share Permitted
CC BY-NC-SA
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The goal of this course is to teach both the fundamentals of nuclear cell biology as well as the methodological and experimental approaches upon which they are based. Lectures and class discussions will cover the background and fundamental findings in a particular area of nuclear cell biology. The assigned readings will provide concrete examples of the experimental approaches and logic used to establish these findings. Some examples of topics include genome and systems biology, transcription, and gene expression.

Subject:
Biology
Life Science
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Sharp, Phillip
Young, Richard
Date Added:
01/01/2010
Computational Functional Genomics, Spring 2005
Conditional Remix & Share Permitted
CC BY-NC-SA
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Study and discussion of computational approaches and algorithms for contemporary problems in functional genomics. Topics include DNA chip design, experimental data normalization, expression data representation standards, proteomics, gene clustering, self-organizing maps, Boolean networks, statistical graph models, Bayesian network models, continuous dynamic models, statistical metrics for model validation, model elaboration, experiment planning, and the computational complexity of functional genomics problems.

Subject:
Biology
Computer Science
Information Technology
Life Science
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Gifford, David
Jaakkola, Tommi Sakari
Date Added:
01/01/2005