Computational biology / bioinformatics

Tools for Chemical Product Design: From Consumer Products to Biomedicine describes the challenges involved in systematic product design across a variety of industries and provides a comprehensive overview of mathematical tools aimed at the design of chemical products, from molecular design to customer products.

Fundamentals and Analytical Applications of Multi-Way Calibration presents researchers with a set of effective tools they can use to obtain the maximum information from instrumental data.

26th European Symposium on Computer Aided Process Engineering contains the papers presented at the 26th European Society of Computer-Aided Process Engineering (ESCAPE) Event held at Portoroz Slovenia, from June 12th to June 15th, 2016.

PDE Modeling of Tissue Engineering and Regenerative Medicine: Computer Analysis in R presents the formulation and computer implementation of mathematical models for the forefront research areas of tissue engineering and regenerative medicine.

Applications of Artificial Intelligence in Medical Imaging provides the description of various biomedical image analysis in disease detection using AI that can be used to incorporate knowledge obtained from different medical imaging devices such as CT, X-ray, PET and ultrasound.

The idea for this book came from the time the authors spent at the Statistics and Applied Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina starting in fall 2003.

Bioinformatics is a relatively new field of research.

Farming Human Pathogens: Ecological Resilience and Evolutionary Process introduces a cutting-edge mathematical formalism based on the asymptotic limit theorems of information theory to describe how punctuated shifts in mesoscale ecosystems can entrain patterns of gene expression and organismal evolution.

Bioinformatics is an evolving field that is gaining popularity due to genomics, proteomics and other high-throughput biological methods.

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework.

There has been a long history of interaction  between mathematics and physiology.

Innate immunity is one the most evolutionally conserved systems, designed to protect the organism from viruses and bacterial infections, stress and many other types of attacks from the outside world.

This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics.

Dynamic-clamp is a fascinating electrophysiology technique that consists of merging living neurons with computational models.

This monograph presents a general mathematical theory for biological growth.

This book applies methods from nonlinear dynamics to problems in neuroscience.

In Risk Analysis of Complex and Uncertain Systems acknowledged risk authority Tony Cox shows all risk practitioners how Quantitative Risk Assessment (QRA) can be used to improve risk management decisions and policies.

In recent years there has been an explosion of network data - that is, measu- ments that are either of or from a system conceptualized as a network - from se- ingly all corners of science.

The papers in this volume comprise the refereed proceedings of the First Int- national Conference on Computer and Computing Technologies in Agriculture (CCTA 2007), in Wuyishan, China, 2007.

The papers in this volume comprise the refereed proceedings of the the First International Conference on Computer and Computing Technologies in Ag- culture (CCTA 2007), in Wuyishan, China, 2007.

Bioconductor software has become a standard tool for the analysis and comprehension of data from high-throughput genomics experiments.

In this monograph, new combinatorial and computational approaches in the study of RNA structures are presented which enhance both mathematics and computational biology.

Introduction to Computational Cardiology provides a comprehensive, in-depth treatment of the fundamental concepts and research challenges involved in the mathematical modeling and computer simulation of dynamical processes in the heart, under normal and pathological conditions.

This book is an overview of mathematical physiology.

One of the "e;image"e; problems with wavelets is that because they have been a dominant area of interest (in nonparametric smoothing) people have forgotten that they are general tools with a fascinating role and future in other areas.

The study of brain function is one of the most fascinating pursuits of m- ern science.

Our basic question is: Given a collection of DNA sequences, what underlying forces are responsible for the observed patterns of variability?

The purpose of this book is to examine the etiology of cancer in large human populations using mathematical models developed from an inter-disciplinary perspective of the population epidemiological, biodemographic, genetic and physiological basis of the mechanisms of cancer initiation and progression.

Sir Francis Crick would undoubtedly be at the front of the line ordering this fascinating book.

Two important types of models for reliability and genetics, the semi-Markov and hidden semi-Markov models are presented in this book.

This book provides balanced coverage of the existing results on sequence data mining as well as pattern types and associated pattern mining methods.

This book is about using interactive and dynamic plots on a computer screen as part of data exploration and modeling, both alone and as a partner with static graphics and non-graphical computational methods.

Biological and biomedical sciences are becoming more interdisciplinary, and scientists of the future need inte rdisciplinary training instead of the conventional disciplinary training.

This text presents mathematical biology as a field with a unity of its own, rather than only the intrusion of one science into another.

Immunoinformatics uses mathematics, information science, computer engineering, genomics, proteomics, and immunological methods to bridge immunology and informatics.

This volume focuses on protein structure prediction methods and describes homology-based structure modeling, fold recognition of globular proteins, ab initio protein structure prediction, structure prediction of membrane proteins, prediction of structures of protein complexes, protein structure-based drug design, and structure prediction as a systems problem.

Systems biology and computational biology have recently become prominent areas of research in the biomedical community, especially in the area of cell biology.

An ultimate goal of modern biology is to understand how the genetic blueprint of cells(genotype)determinesthestructure,function,andbehaviorofalivingorganism (phenotype).

Most traits in nature and of importance to agriculture are quantitatively inherited.

Gene mapping is used in experimental genetics to improve the hardiness or productivity of animals or plants of agricultural value, to explore basic mechanisms of inheritance, or to study animal models of human inheritance.

This book provides a detailed account of the theoretical foundations of proposed multiple testing methods and illustrates their application to a range of testing problems in genomics.

The rapid growth of the Web has led to the proliferation of information sources and content accessible via the Internet.

Computational Neurogenetic Modeling is a student text, introducing the scope and problems of a new scientific discipline - Computational Neurogenetic Modeling (CNGM).

A Computer Scientist's Guide to Cell Biology provides a "e;reading knowledge"e; of biology to those coming into the field from the perspective of computer science-particularly from the areas of information retrieval and/or machine learning.

As natural phenomena are being probed and mapped in ever-greater detail, scientists in genomics and proteomics are facing an exponentially growing vol- ume of increasingly complex-structured data, information, and knowledge.

Whatever its final readership and impact, we, the Editors, feel this book is im- portant.

April 2006 Introduction Bioinformatics is at a crossroads.

As a result, the inference of phylogenies often seems divorced from any connection to other methods of analysis of scienti?

As studies using microarray technology have evolved, so have the data analysis methods used to analyze these experiments.

The past decade has seen powerful new computational tools for modeling which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains.