Modeling and simulation of biological networks : American Mathematical Society January 10-11, 2006 San Antonio, Texas / Reinhard C. Laubenbacher, editor.

Format:

Book

Author/Creator:

American Mathematical Society Short Course, Modeling and Simulation of Biological Networks, Corporate Author.

Contributor:

Laubenbacher, Reinhard, editor.

American Mathematical Society. Short Course, organizer of meeting.

Series:

Proceedings of symposia in applied mathematics. AMS short course lecture notes ; Volume 64.

Proceedings of Symposia in Applied Mathematics : AMS Short Course Lecture Notes ; Volume 64

Language:

English

Subjects (All):

Biology--Mathematical models--Congresses.

Biology.

Computational biology--Congresses.

Computational biology.

Physical Description:

1 online resource (160 p.)

Place of Publication:

Providence, Rhode Island : American Mathematical Society, 2007.

Language Note:

English

Summary:

It is the task of computational biology to help elucidate the unique characteristics of biological systems. This process has barely begun, and many researchers are testing computational tools that have been used successfully in other fields. Mathematical and statistical network modeling is an important step toward uncovering the organizational principles and dynamic behavior of biological networks. Undoubtedly, new mathematical tools will be needed, however, to meet this challenge. The workhorse of this effort at present comprises the standard tools from applied mathematics, which have proven to be successful for many problems. But new areas of mathematics not traditionally considered applicable are contributing other powerful tools. This volume is intended to introduce this topic to a broad mathematical audience. The aim is to explain some of the biology and the computational and mathematical challenges we are facing. The different chapters provide examples of how these challenges are met, with particular emphasis on nontraditional mathematical approaches.The volume features a broad spectrum of networks across scales, ranging from biochemical networks within a single cell to epidemiological networks encompassing whole cities. Chapter topics include phylogenetics and gene finding using tools from statistics and algebraic geometry, biochemical network inference using tools from computational algebra, control-theoretic approaches to drug delivery using differential equations, and interaction-based modeling and discrete mathematics applied to problems in population dynamics and epidemiology.

Contents:

""Contents""; ""Introduction to Modeling and Simulation of Biological Networks""; ""An introduction to reconstructing ancestral genomes""; ""Phylogenetics""; ""Polynomial dynamical systems in systems biology""; ""An introduction to optimal control applied to immunology problems""; ""Modeling and simulation of large biological, information and socio-technical systems: An interaction-based approach""; ""Index""; ""A""; ""B""; ""C""; ""D""; ""E""; ""F""; ""G""; ""H""; ""I""; ""J""; ""K""; ""L""; ""M""; ""N""; ""O""; ""P""; ""R""; ""S""; ""T""; ""U""; ""V""; ""W""; ""Y""

Notes:

Description based upon print version of record.

Includes bibliographical references at the end of each chapters and index.

Description based on print version record.

ISBN:

0-8218-9279-7