Structured Biological Modelling presents a straightforward introduction for computer-aided analysis, mathematical modelling, and simulation of cell biological systems. This unique guide brings together the physiological, structural, molecular biological, and theoretical aspects of the signal transduction network that regulates growth and proliferation in normal and tumor cells. It provides comprehensive survey of functional and theoretical features of intracellular signal processing and introduces the concept of cellular self-organization. Exemplified by oscillatory calcium waves, strategies for the design of computer experiments are presented that can assist or even substitute for time-consuming biological experiments. The presented minimal model for proliferation-associated signal transduction clearly shows the alterations of the cellular signal network involved in neoplastic growth. This book will be useful to cell and molecular biologists, oncologists, physiologists, theoretical biologists, computer scientists, and all other researchers and students studying functional aspects of cellular signaling.
Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high-throughput bioinformatics data arising from problems in molecular and structural biology and disease ...
This book deals with the recent and important advances in the study of structured population models in biology and epidemiology. There are six chapters in this book, written by leading researchers in these areas.
Smith and Thieme (2013) extended the results of Rebarber et al. (2012) in several directions. First, they studied a generalization of (5.4.1) in which survival is not necessarily modeled with a smooth kernel.
Pearson. chi-squared. statistic,. X(O. -. E)*/E,. where. O. denotes. observed. and. E denotes expected frequencies. As with the deviance, the degrees of freedom are usually taken as Nā 1āp, where N is the total number of frequencies and ...
(Adapted from L Liu, LMI Koharudin, AM Gronenborn, and I Bahar. Proteins, 77:927ā939, 2009.) so that that the average fluctuations of a protein's residues are approximately equal to the average B-factors. Across proteins, it is found ...
This text is intended to fill that gap by teaching students how to reason about developing formal mathematical models of biological systems that are amenable to computational analysis.
Homology modeling is an in silico method that predicts the tertiary structure of an amino acid sequence based on a homologous experimentally determined structure.
Within those four sections, the following topics are covered: Databases and resources that are commonly used for protein structure prediction The structure prediction flagship assessment (CASP) and the protein structure initiative (PSI) ...
Computational Molecular modelling in Structural Biology, Volume 113, the latest release in the Advances in Protein Chemistry and Structural Biology, highlights new advances in the field, with this new volume presenting interesting chapters ...
This book provides an overview of the established computational methods used for modeling biologically and medically relevant systems.