Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

In recent years, technological breakthroughs have greatly enhanced our ability to understand the complex world of molecular biology. Rapid developments in genomic profiling techniques, such as high-throughput sequencing, have brought new opportunities and challenges to the fields of computational biology and bioinformatics. Furthermore, by combining genomic profiling techniques with other experimental techniques, many powerful approaches (e.g., RNA-Seq, Chips-Seq, single-cell assays, and Hi-C) have been developed in order to help explore complex biological systems. As a result of the increasing availability of genomic datasets, in terms of both volume and variety, the analysis of such data has become a critical challenge as well as a topic of great interest. Therefore, statistical methods that address the problems associated with these newly developed techniques are in high demand. This book includes a number of studies that highlight the state-of-the-art statistical methods for the analysis of genomic data and explore future directions for improvement.

multiple cancer types --- integrative analysis --- omics data --- prognosis modeling --- classification --- gene set enrichment analysis --- boosting --- kernel method --- Bayes factor --- Bayesian mixed-effect model --- CpG sites --- DNA methylation --- Ordinal responses --- GEE --- lipid–environment interaction --- longitudinal lipidomics study --- penalized variable selection --- convolutional neural networks --- deep learning --- feed-forward neural networks --- machine learning --- gene regulatory network --- nonparanormal graphical model --- network substructure --- false discovery rate control --- gaussian finite mixture model --- clustering analysis --- uncertainty --- expectation-maximization algorithm --- classification boundary --- gene expression --- RNA-seq --- n/a --- lipid-environment interaction

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book discusses the core principles and practical applications of a brand new machine category: liquid-metal soft machines and motors. After a brief introduction on the conventional soft robot and its allied materials, it presents the new conceptual liquid-metal machine, which revolutionizes existing rigid robots, both large and small. It outlines the typical features of the soft liquid-metal materials and describes the various transformation capabilities, mergence of separate metal droplets, self-rotation and planar locomotion of liquid-metal objects under external or internal mechanism. Further, it introduces a series of unusual phenomena discovered while developing the shape changeable smart soft machine and interprets the related mechanisms regarding the effects of the shape, size, voltage, orientation and geometries of the external fields to control the liquid-metal transformers. Moreover, the book illustrates typical strategies to construct a group of different advanced functional liquid-metal soft machines, since such machines or robots are hard to fabricate using rigid-metal or conventional materials. With highly significant fundamental and practical findings, this book is intended for researchers interested in establishing a general method for making future smart soft machine and accompanying robots.

Liquid metals. --- Materials. --- Artificial intelligence. --- Engineering. --- Biomedical engineering. --- Hydraulic engineering. --- Metallic Materials. --- Artificial Intelligence. --- Robotics and Automation. --- Machinery and Machine Elements. --- Biomedical Engineering and Bioengineering. --- Engineering Fluid Dynamics. --- Engineering, Hydraulic --- Engineering --- Fluid mechanics --- Hydraulics --- Shore protection --- Clinical engineering --- Medical engineering --- Bioengineering --- Biophysics --- Medicine --- Construction --- Industrial arts --- Technology --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Engineering materials --- Industrial materials --- Engineering design --- Manufacturing processes --- Materials --- Metals. --- Robotics. --- Automation. --- Machinery. --- Fluid mechanics. --- Hydromechanics --- Continuum mechanics --- Machinery --- Machines --- Manufactures --- Power (Mechanics) --- Mechanical engineering --- Motors --- Power transmission --- Automatic factories --- Automatic production --- Computer control --- Engineering cybernetics --- Factories --- Industrial engineering --- Mechanization --- Assembly-line methods --- Automatic control --- Automatic machinery --- CAD/CAM systems --- Robotics --- Automation --- Metallic elements --- Chemical elements --- Ores --- Metallurgy --- Curious devices

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Fluid mechanics --- Metals and their compounds --- Human biochemistry --- Hydraulic energy --- Machine elements --- Applied physical engineering --- Biotechnology --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- medische biochemie --- bio-engineering --- automatisering --- biotechnologie --- KI (kunstmatige intelligentie) --- machines --- ingenieurswetenschappen --- metalen --- robots --- hydraulica --- vloeistoffen