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Introduction to mathematics for computational biology
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Introduction to mathematics for computational biology/ by Paola Lecca, Bruno Carpentieri.
作者:
Lecca, Paola.
其他作者:
Carpentieri, B.
出版者:
Cham :Springer International Publishing : : 2023.,
面頁冊數:
x, 264 p. :ill., digital ; : 24 cm.;
Contained By:
Springer Nature eBook
標題:
Biophysical Methods. -
電子資源:
https://doi.org/10.1007/978-3-031-36566-9
ISBN:
9783031365669
Introduction to mathematics for computational biology
Lecca, Paola.
Introduction to mathematics for computational biology
[electronic resource] /by Paola Lecca, Bruno Carpentieri. - Cham :Springer International Publishing :2023. - x, 264 p. :ill., digital ;24 cm. - Techniques in life science and biomedicine for the non-expert,2367-1122. - Techniques in life science and biomedicine for the non-expert..
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 --.
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.
ISBN: 9783031365669
Standard No.: 10.1007/978-3-031-36566-9doiSubjects--Topical Terms:
1392449
Biophysical Methods.
LC Class. No.: QH324.2
Dewey Class. No.: 570.285
Introduction to mathematics for computational biology
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