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020 _a9783031365669
024 7 _a10.1007/978-3-031-36566-9
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aQH324.2
_b2023 EB
100 1 _aLecca, Paola
_d1973-
_eautor
_0(orcid)0000-0002-7224-136X
_1https://orcid.org/0000-0002-7224-136X
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9689786
245 1 0 _aIntroduction to Mathematics for Computational Biology
_cby Paola Lecca, Bruno Carpentieri
250 _a1st ed. 2023
264 1 _aCham
_bSpringer International Publishing
_c2023
300 _a1 recurso en línea
336 _atexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
490 0 _aTechniques in Life Science and Biomedicine for the Non-Expert
_x2367-1122
505 0 _a1. 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 -- .
520 _aThis 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. .
988 _aSpringer_BiomedLife_2023
650 7 _2embne
_9160489
_aBioinformática
700 1 _9689787
_aCarpentieri, Bruno
_eautor
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-36566-9
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _b03/2024
_dz
_eb
_zSI