الصفحة 1
الصفحة 1
Markov Chains : Models, Algorithms and Applications
Markov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems over time. This monograph will present a series of Markov models, starting from the basic models and then building up to higher-order models. Included in the higher-order discussions are multivariate models, higher-order multivariate models, and higher-order hidden models. In each case, the focus is on the important kinds of applications that can be made with the class of models being considered in the current chapter. Special attention is given to numerical algorithms that can efficiently solve the models. Therefore, Markov Chains: Models, Algorithms and Applications outlines recent developments of Markov chain models for modeling queueing sequences, Internet, re-manufacturing systems, reverse logistics, inventory systems, bio-informatics, DNA sequences, genetic networks, data mining, and many other practical systems.
Comparative genomics ; Vol.4205 ; RECOMB 2006 International Workshop, RECOMB-CG 2006, Montreal, Canada, September 24-26, 2006, Proceedings
The papers address a broad variety of aspects and components of the field of comparative genomics, ranging from new quantitative discoveries about genome structure and process to theorems on the complexity of computational problems inspired by genome comparison.
Comparative genomics ; RECOMB 2007, International Workshop, RECOMB-CG 2007, San Diego, CA, USA, September 16-18, 2007, Proceedings
This book provides an evolutionary conceptual framework for comparative genomics, with the ultimate objective of understanding the loss and gain of genes during evolution, the interactions among gene products, and the relationship between genotype, phenotype and the environment. The many examples in the book have been carefully chosen from primary research literature based on two criteria: their biological insight and their pedagogical merit. The phylogeny-based comparative methods, involving both continuous and discrete variables, often represent a stumbling block for many students entering the field of comparative genomics. They are numerically illustrated and explained in great detail.
