Programming knowledge is often necessary for finding a solution to a biological problem. Based on the author’s extensive experience, Python for Bioinformatics helps scientists solve their biological p
The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new comput
Exome and genome sequencing are revolutionizing medical research and diagnostics, but the computational analysis of the data has become an extremely heterogeneous and often challenging area of bioinfo
This self-contained book focuses on three categories of disease: cancer, viral diseases, and dynamical diseases. It presents the medical and biological background of the diseases, specific issues to b
The future of cancer research and the development of new therapeutic strategies rely on our ability to convert biological and clinical questions into mathematical models—integrating our knowledge of t
This text covers the main aspects of systems biology from a systems theoretical point of view. Systems biology is an emerging research field that incorporates methods and tools from molecular biology,
This book covers the use of mathematical models in ecology, particularly factors that affect herbivory. The aim is to provide models that are motivated by and can be used for evaluation of alternative
This book emphasizes computer programs that analyze protein structural data with program output generating data files and visual feedback in the form of a molecular display. The theoretical part of th
In the past three decades, considerable progress has been made in the mathematical analysis, modelling, and simulation of the fluid dynamics of liquid capsules and biological cells, and interest in th
Introduction to Proteins shows how proteins can be analyzed in multiple ways. It refers to the roles of proteins and enzymes in diverse contexts and everyday applications, including medical disorders,
Unique in its coverage of Bayesian phylogenics, this book covers advances in statistics as applied to the field of phylogenetics and coalescence-based population genetics. It is designed for statistic
The book is designed for upper level under-graduates, graduate students and researchers in various STEM disciplines interested in performing efficient and cost effective image acquisition and processi
Big Data in Omics and Imaging: Association Analysis addresses the recent development of association analysis and machine learning for both population and family genomic data in sequencing era. It is u
Big Data offers both unprecedented opportunities and overwhelming challenges. This book is intended to provide biologists, biomedical scientists, bioinformaticians and computer data analysts a pragmat
The goal of this introductory graduate textbook is to cover the statistical and computational methods needed by molecular biologists in order to analyze their own data without the help of a bioinforma
