Introduction to Mathematics for Computational Biology [electronic resource] / by Paola Lecca, Bruno Carpentieri.

By:

Lecca, Paola [author.]

Contributor(s):

Carpentieri, Bruno [author.]

Material type: Text

TextLanguage: English Series: Publication details: Cham : Springer International Publishing : Imprint: Springer, 2023.Edition: 1st ed. 2023Description: X, 264 p. 40 illus., 30 illus. in color. online resourceISBN:

9783031365669

Subject(s):

DDC classification:

570.285 23
570.113 23

Online resources:

Click Here

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. .

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Holdings
Item type	Current library	Call number	Materials specified	Status	Date due	Barcode	Item holds
E-Books	National Library of India Online Resource	570.285 \| 570.113 (Browse shelf(Opens below))		Available		EBK000045721ENG

Total holds: 0

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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