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Paperback. Condition: new. Paperback. A hands-on lab guide in the Python programming language that enables students in the life sciences to reason quantitatively about living systems across scales.This lab guide accompanies the textbook Quantitative Biosciences, providing students with the skills they need to translate biological principles and mathematical concepts into computational models of living systems. This hands-on guide uses a case study approach organised around central questions in the life sciences, introducing landmark advances in the field while teaching students - whether from the life sciences, physics, computational sciences, engineering, or mathematics - how to reason quantitatively in the face of uncertainty. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Add to basketPaperback. Condition: New. A hands-on lab guide in the Python programming language that enables students in the life sciences to reason quantitatively about living systems across scalesThis lab guide accompanies the textbook Quantitative Biosciences, providing students with the skills they need to translate biological principles and mathematical concepts into computational models of living systems. This hands-on guide uses a case study approach organized around central questions in the life sciences, introducing landmark advances in the field while teaching students-whether from the life sciences, physics, computational sciences, engineering, or mathematics-how to reason quantitatively in the face of uncertainty.Draws on real-world case studies in molecular and cellular biosciences, organismal behavior and physiology, and populations and ecological communitiesEncourages good coding practices, clear and understandable modeling, and accessible presentation of resultsHelps students to develop a diverse repertoire of simulation approaches, enabling them to model at the appropriate scaleBuilds practical expertise in a range of methods, including sampling from probability distributions, stochastic branching processes, continuous time modeling, Markov chains, bifurcation analysis, partial differential equations, and agent-based simulationsBridges the gap between the classroom and research discovery, helping students to think independently, troubleshoot and resolve problems, and embark on research of their ownStand-alone computational lab guides for Quantitative Biosciences also available in R and MATLAB.
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Add to basketPaperback. Condition: new. Paperback. A hands-on lab guide in the Python programming language that enables students in the life sciences to reason quantitatively about living systems across scales.This lab guide accompanies the textbook Quantitative Biosciences, providing students with the skills they need to translate biological principles and mathematical concepts into computational models of living systems. This hands-on guide uses a case study approach organised around central questions in the life sciences, introducing landmark advances in the field while teaching students - whether from the life sciences, physics, computational sciences, engineering, or mathematics - how to reason quantitatively in the face of uncertainty. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Add to basketCondition: New. Über den AutorJoshua S. Weitz, Nolan English, Alexander B. Lee, and Ali ZamaniKlappentextA hands-on lab guide in the Python programming language that enables students in the life sciences to reason quanti.
Published by Princeton University Press, New Jersey, 2024
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Add to basketPaperback. Condition: new. Paperback. A hands-on lab guide in the Python programming language that enables students in the life sciences to reason quantitatively about living systems across scales.This lab guide accompanies the textbook Quantitative Biosciences, providing students with the skills they need to translate biological principles and mathematical concepts into computational models of living systems. This hands-on guide uses a case study approach organised around central questions in the life sciences, introducing landmark advances in the field while teaching students - whether from the life sciences, physics, computational sciences, engineering, or mathematics - how to reason quantitatively in the face of uncertainty. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Add to basketTaschenbuch. Condition: Neu. Neuware - A hands-on lab guide in the Python programming language that enables students in the life sciences to reason quantitatively about living systems across scalesThis lab guide accompanies the textbook Quantitative Biosciences, providing students with the skills they need to translate biological principles and mathematical concepts into computational models of living systems. This hands-on guide uses a case study approach organized around central questions in the life sciences, introducing landmark advances in the field while teaching students-whether from the life sciences, physics, computational sciences, engineering, or mathematics-how to reason quantitatively in the face of uncertainty.
Published by Princeton University Press, 2024
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Add to basketTaschenbuch. Condition: Neu. Quantitative Biosciences Companion in Python | Dynamics Across Cells, Organisms, and Populations | Joshua S Weitz (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | Princeton University Press | EAN 9780691255675 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Published by Princeton University Press, US, 2024
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Add to basketPaperback. Condition: New. A hands-on lab guide in the Python programming language that enables students in the life sciences to reason quantitatively about living systems across scalesThis lab guide accompanies the textbook Quantitative Biosciences, providing students with the skills they need to translate biological principles and mathematical concepts into computational models of living systems. This hands-on guide uses a case study approach organized around central questions in the life sciences, introducing landmark advances in the field while teaching students-whether from the life sciences, physics, computational sciences, engineering, or mathematics-how to reason quantitatively in the face of uncertainty.Draws on real-world case studies in molecular and cellular biosciences, organismal behavior and physiology, and populations and ecological communitiesEncourages good coding practices, clear and understandable modeling, and accessible presentation of resultsHelps students to develop a diverse repertoire of simulation approaches, enabling them to model at the appropriate scaleBuilds practical expertise in a range of methods, including sampling from probability distributions, stochastic branching processes, continuous time modeling, Markov chains, bifurcation analysis, partial differential equations, and agent-based simulationsBridges the gap between the classroom and research discovery, helping students to think independently, troubleshoot and resolve problems, and embark on research of their ownStand-alone computational lab guides for Quantitative Biosciences also available in R and MATLAB.
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