Energy Autonomy of Real-Time Systems addresses foundations and findings in real-time scheduling and processor activity management for energy harvesting embedded systems, serving as a textbook for courses on the topic in master programs, and as a reference for computer scientists and engineers involved in the design or development of autonomous cyber-physical systems which require up-to-date solutions.
This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2021, held on September 27, 2021, in conjunction with MICCAI 2021.
This two-volume set LNCS 10305 and LNCS 10306 constitutes the refereed proceedings of the 15th International Work-Conference on Artificial Neural Networks, IWANN 2019, held at Gran Canaria, Spain, in June 2019.
This textbook takes you from the very first time you open MATLAB(R) through to a position where you can comfortably integrate this computer language into your research or studies.
Designing User Interfaces for an Aging Population: Towards Universal Design presents age-friendly design guidelines that are well-established, agreed-upon, research-based, actionable, and applicable across a variety of modern technology platforms.
This book is a concise but thorough introduction to the tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as well as recent popular topics such as deep neural networks and Gaussian process regression.
Resolving Spectral Mixtures: With Applications from Ultrafast Time-Resolved Spectroscopy to Superresolution Imaging offers a comprehensive look into the most important models and frameworks essential to resolving the spectral unmixing problem-from multivariate curve resolution and multi-way analysis to Bayesian positive source separation and nonlinear unmixing.
This second edition provides new and updated chapters describing the utility and attributes of different tools that are used for studying microbial systems.
This detailed book provides an overview of various classes of computational techniques, including machine learning techniques, commonly used for evaluating kinetic parameters of biological systems.
This new edition explores lab protocols describing new techniques to study cytotoxic T-cells (CTLs), as well as chapters of a more general discursive nature, all with an emphasis on the use of systems biology in immunology.
This volume addresses the latest state-of-the-art systems biology-oriented approaches that--driven by big data and bioinformatics--are utilized by Computational Systems Biology, an interdisciplinary field that bridges experimental tools with computational tools to tackle complex questions at the frontiers of knowledge in medicine and biotechnology.
This volume focuses on a variety of in silico protocols of the latest bioinformatics tools and computational pipelines developed for neo-antigen identification and immune cell analysis from high-throughput sequencing data for cancer immunotherapy.
This thorough new edition explores web servers and software for protein structure prediction and modeling that are freely available to the academic community.
This book provides a comprehensive guide to scientists, engineers, and students that employ metabolomics in their work, with an emphasis on the understanding and interpretation of the data.
This manual provides insights into the theory and practical aspects of several biotechnological and biochemical techniques for plants, protozoa, nematodes, insects and fishes, as well as human samples.
Emerging Practices in Telehealth: Best Practices in a Rapidly Changing Field is an introduction to telehealth basics, best practices and implementation methods.
Computational Modeling of Infectious Disease: With Applications in Python provides an illustrated compendium of tools and tactics for analyzing infectious diseases using cutting-edge computational methods.
This volume details state-of-art eQTL analysis, where interdisciplinary researchers are provided both theoretical and practical guidance to eQTL analysis and interpretation.
This second edition provides new and updated chapters from expert researchers in the field detailing methods used to study the multi-facet deep sequencing data field.
This volume presents state-of-the art design, analysis and integration approaches for biomedical data including novel statistical models for a comprehensive and powerful synthesis and assessment of scientific evidence.
This volume introduces Translational Bioinformatics as it relates to therapeutic development, and addresses the techniques needed to effectively translate large data sets to relevant biological networks.
This meticulous book explores the leading methodologies, techniques, and tools for microarray data analysis, given the difficulty of harnessing the enormous amount of data.
This detailed collection explores genome-wide association studies (GWAS), which have revolutionized the investigation of complex traits over the past decade and have unveiled numerous useful genotype-phenotype associations in plants.
This book provides a single-source reference on the current state of the ribosome profiling method by describing experimental protocols for the quantitative analysis of translation in a variety of model organisms.
This volume focuses on computational modeling of the ecotoxicity of chemicals and presents applications of quantitative structure-activity relationship models (QSARs) in the predictive toxicology field in a regulatory context.
This thorough book provides a collection of techniques used in the emerging field of computational chemogenomics, which is an integration of chemoinformatics, bioinformatics, computer science, statistics, automated pattern recognition and modeling, database usage with data retrieval, and systems integration.
