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
Data Science and Analytics with Python is designed for practitioners in data science and data analytics in both academic and business environments. The aim is to present the reader with the main conce
The typical computational approach to object understanding derives shape information from the 2D outline of the objects. For complex object structures, however, such a planar approach cannot determine
The integration and convergence of state-of-the-art technologies in the grid have enabled more flexible, automatic, and complex grid services to fulfill industrial and commercial needs, from the LHC a
Setting out the principles of stereology from a statistical viewpoint, this book focuses on both basic theory and practical implications. The authors discuss ways to effectively communicate statistica
With contributions from some of the leading authorities in the field, the work in Differential Equations: Inverse and Direct Problems stimulates the preparation of new research results and offers exci
Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of stat
Introductory in its approach, this text covers essential aspects of research methods. The author emphasizes major topics, such as experimental design, scale construction techniques, testing reliabilit
Spectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying existing feature selection algorithms and developing new algo
Fundamentals of Dependable Computing for Software Engineers presents the essential elements of computer system dependability. The book describes a comprehensive dependability-engineering process and e
Writing for advanced undergraduates, Cain and Meyer (both mathematics emeriti, Georgia Institute of Technology) introduce a computable separation of variables solutions as an analytic approximate solu
Clear, concise, and organized, Multivariate Analysis with MATLAB and R provides a self-contained introduction to the field of multivariate analysis. Integrating practical computations, the book explai
Considered a key indicator of the progress and current state of the field, the TOP500 list has become a globally recognized tool for classifying technology trends in high-performance computing (HPC).
Developing applications that scale well on massively parallel architectures is quite difficult, due to problems with synchronization and communication time as well as fault tolerance. This book review
A Modern Framework Based on Time-Tested MaterialA Functional Analysis Framework for Modeling, Estimation and Control in Science and Engineering presents functional analysis as a tool for understanding
LabVIEW™ has become one of the preeminent platforms for the development of data acquisition and data analysis programs. LabVIEW™: A Developer’s Guide to Real World Integration explai
This book describes the coarray parallel programming model that will be part of the next standard version of the Fortran language. It provides a practical guide for Fortran programmers who want to sta
Statistical Methods for Long Term Memory Processes covers the diverse statistical methods and applications for data with long-range dependence. Presenting material that previously appeared only in jou
