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Statistical Optimization of Biological Systems

essence of a genetic algorithm Statistical Optimization of Biological Systems examines the complex nature of biological systems, the need for;

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Statistical Methods for Spatio-Temporal Systems

Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will;

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Dynamical Systems for Biological Modeling

Dynamical Systems for Biological Modeling: An Introduction prepares both biology and mathematics students with the understanding and;

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Statistical Methods Of Spatio-Temporal Systems

Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will;

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Gene Expression Data Analysis

for generating gene expression data. Background knowledge on statistical modeling and machine learning techniques. Detailed methodology;

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Analysis of Biological Systems

Modeling is fast becoming fundamental to understanding the processes that define biological systems. High-throughput technologies are;

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Computational Modeling of Biological Systems

Computational modeling is emerging as a powerful new approach to study and manipulate biological systems. Multiple methods have been;

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Hybrid Systems Biology

information including learning for biological systems, parametric synthesis and inference; stochastic and hybrid models in biology; hierarchical;

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Computational Systems Bioinformatics - Methods And Biomedical Applications

of biological systems at the molecular, cellular, tissue, and organ levels through computational modeling as well as novel information theoretic data;

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Towards A Mathematical Theory Of Complex Biological Systems

of living systems, especially biological systems, will appreciate the special class of integro-differential equations offered here for modeling at;

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Handbook of Statistical Systems Biology

in mathematical models of biological systems. The area is moving towards a full statistical analysis and probabilistic reasoning over the inferences that;

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Modeling Solvent Environments: Applications to Simulations of Biomolecules

A comprehensive view of the current methods for modeling solvent environments with contributions from the leading researchers in the field;

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Computational Methods in Systems Biology

37 regular paper submissions. The topics include formalisms for modeling biological processes; models and their biological applications;

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Statistical Physics for Biological Matter

), soft matter and fluid physics, for applications to biological phenomena at both cellular and macromolecular levels. It is intended to be a;

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Computational Methods in Systems Biology

submissions. Topics of interest include formalisms for modeling biological processes; models and their biological applications; frameworks for model;

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Statistical Methods for the Evaluation of University Systems

include: statistical methods for constructing composite indicators, applied measurements, assessment of educational systems, measurement of the;

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Semimartingales and their Statistical Inference

applications to engineering and economic systems, financial economics, and the biological and medical sciences have made statistical inference for;

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Semimartingales and Their Statistical Inference

applications to engineering and economic systems, financial economics, and the biological and medical sciences have made statistical inference for;

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Computational Methods in Systems Biology

carefully reviewed and selected from 41 regular paper submissions. Topics of interest include formalisms for modeling biological processes; models;

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Networks in Systems Biology

This book presents a range of current research topics in biological network modeling, as well as its application in studies on human hosts;

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Modeling and Analysis of Bio molecular Networks

number of statistical methods for exploring important bioinformatics applications, including the identification of significant bio-molecules for;

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Modeling and Analysis of Bio molecular Networks

number of statistical methods for exploring important bioinformatics applications, including the identification of significant bio-molecules for;

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A Cell Biologist's Guide to Modeling and Bioinformatics

searches for sequence similarity, protein families, and putative functional domains. Discussions of sequence alignments and biological database;

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Statistical Physics

The book is divided into two parts. The first part looks at the modeling of statistical systems before moving on to an analysis of these;

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Computational Methods in Systems Biology

biological processes; models and their biological applications; frameworks for model verification, validation, analysis, and simulation of biological;

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Statistical Physics of Complex Systems

This third edition of Statistical Physics of Complex Systems has been expanded to provide more examples of applications of concepts and;

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Multiscale Signal Analysis and Modeling

, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and;

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