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A Stochastic Model for Immunological Feedback in Carcinogenesis: Analysis and Approximations

A Stochastic Model for Immunological Feedback in Carcinogenesis: Analysis and Approximations

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"A Stochastic Model for Immunological Feedback in Carcinogenesis: Analysis and Approximations" by N. Dubin is a mathematics book and learning resource focused on Core Mathematics. Best for teachers, students, and readers looking for stronger mathematical understanding.

Stochastic processes often pose the difficulty that, as soon as a model devi ates from the simplest kinds of assumptions, the differential equations obtained for the density and the generating functions become mathematically formidable. Worse still, one is very often led to equations which have no known solution and don't yield to standard analytical methods for differential equations. In the model considered here, one for tumor growth with an immunological re sponse from the normal tissue, a nonlinear term in the transition probability for the death of a tumor cell leads to the above-mentioned complications. Despite the mathematical disadvantages of this nonlinearity, we are able to consider a more sophisticated model biologically. Ultimately, in order to achieve a more realistic representation of a complicated phenomenon, it is necessary to examine mechanisms which allow the model to deviate from the more mathematically tractable linear format. Thus far, stochastic models for tumor growth have almost exclusively considered linear transition probabilities.

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Best For: Researchers and students interested in mathematical modeling of biological processes, particularly tumor growth and immunology.
Focus: Developing and analyzing a stochastic model that incorporates immunological feedback mechanisms in carcinogenesis.
Covers: Mathematical formulation of stochastic processes related to tumor growth, challenges in solving associated differential equations, and approximation methods.
Why It Matters: Provides insight into complex interactions between tumor development and immune response using advanced mathematical tools, aiding in understanding and potentially improving cancer modeling approaches.

"A Stochastic Model for Immunological Feedback in Carcinogenesis: Analysis and Approximations" by N. Dubin is a mathematics book and learning resource focused on Core Mathematics. Best for teachers, students, and readers looking for stronger mathematical understanding.

Topic: Core Mathematics

Author: N. Dubin

Who this is for:

  • Teachers and classroom instructors
  • Students building subject mastery
  • Readers looking for practical learning support

Why this book matters: It stands out as a practical math resource that helps explain concepts, strengthen problem-solving, and support classroom or independent learning.

Stochastic processes often pose the difficulty that, as soon as a model devi ates from the simplest kinds of assumptions, the differential equations obtained for the density and the generating functions become mathematically formidable. Worse still, one is very often led to equations which have no known solution and don't yield to standard analytical methods for differential equations. In the model considered here, one for tumor growth with an immunological re sponse from the normal tissue, a nonlinear term in the transition probability for the death of a tumor cell leads to the above-mentioned complications. Despite the mathematical disadvantages of this nonlinearity, we are able to consider a more sophisticated model biologically. Ultimately, in order to achieve a more realistic representation of a complicated phenomenon, it is necessary to examine mechanisms which allow the model to deviate from the more mathematically tractable linear format. Thus far, stochastic models for tumor growth have almost exclusively considered linear transition probabilities.

AuthorN. Dubin
PublisherSpringer
Published1976-06
ISBN-139783540077862
BindingPaperback
Pages192
LanguageEnglish
SubjectsGardening
TopicCore Mathematics
SeriesLecture Notes in Biomathematics

Format: Paperback

Length: 192 pages

Language: English

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