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Introduction to Mathematics for Computational Biology [E-Book]

By:

Lecca, Paola [author.]

Contributor(s):

Series: Techniques in Life Science and Biomedicine for the Non-ExpertPublisher: Cham : Springer International Publishing : Imprint: Springer, 2023Edition: 1st ed. 2023Description: X, 264 p. 40 illus., 30 illus. in color. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783031365669

Subject(s):

Online resources:

Access resource

Contents:

1. Introduction to graph theory -- 2. Biological networks -- 3. Network inference for drug discovery- 4. Introduction to differential and integral calculus -- 5. Modelling chemical reactions -- 6. Reaction-diffusion systems -- 7. Linear algebra background -- 8. Regression -- 9. Cardiac electrophysiology -- .

Summary: This introductory guide provides a thorough explanation of the mathematics and algorithms used in standard data analysis techniques within systems biology, biochemistry, and biophysics. Each part of the book covers the mathematical background and practical applications of a given technique. Readers will gain an understanding of the mathematical and algorithmic steps needed to use these software tools appropriately and effectively, as well how to assess their specific circumstance and choose the optimal method and technology. Ideal for students planning for a career in research, early-career researchers, and established scientists undertaking interdiscplinary research. .

Holdings
Item type	Home library	Class number	URL	Status	Date due	Barcode
Electronic book	Hillingdon Hospitals Library Services (Hillingdon Hospitals NHS Foundation) Online		Link to resource	Available

This introductory guide provides a thorough explanation of the mathematics and algorithms used in standard data analysis techniques within systems biology, biochemistry, and biophysics. Each part of the book covers the mathematical background and practical applications of a given technique. Readers will gain an understanding of the mathematical and algorithmic steps needed to use these software tools appropriately and effectively, as well how to assess their specific circumstance and choose the optimal method and technology. Ideal for students planning for a career in research, early-career researchers, and established scientists undertaking interdiscplinary research. .

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