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Data visualization is an essential component of genomic data analysis. However, the size and diversity of the data sets produced by today's sequencing and array-based profiling methods present major challenges to visuali...

1 Introduction 1.1 What is Data Mining? 1.2 Motivating Challenges 1.3 The Origins of Data Mining 1.4 Data Mining Tasks 1.5 Scope and Organization of the Book 1.6 Bibliographic Notes 1.7 Exercises 2 Data 2.1 Types of Data...

With the continuous expansion of data availability in many large-scale, complex, and networked systems, such as surveillance, security, Internet, and finance, it becomes critical to advance the fundamental understanding ...

The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research...

In the past decade, the field of medical image analysis has grown exponentially, with an increased number of pattern recognition tools and an increase in data set sizes. These advances have facilitated the development of...

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together t...

The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world's largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeX...

BACKGROUND: the analysis of microbial communities through dna sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, vis...

Machine learning and data mining techniques have been used in numerous real-world applications. An assumption of traditional machine learning methodologies is the training data and testing data are taken from the same do...

Qualitative content analysis and thematic analysis are two commonly used approaches in data analysis of nursing research, but boundaries between the two have not been clearly specified. In other words, they are being use...

Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existin...

Guidelines for determining nonprobabilistic sample sizes are virtually nonexistent. Purposive samples are the most commonly used form of nonprobabilistic sampling, and their size typically relies on the concept of “sat...

The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer ...

This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and pane...

AIM: The aim of this paper is to distinguish the integrative review method from other review methods and to propose methodological strategies specific to the integrative review method to enhance the rigour of the process...

Fil: Silva, Germán. Universidad Nacional de Quilmes. Departamento de Economía y Administración; Argentina. La asignatura tiene como objetivo la gestión del patrimonio arqueológico para ser ofrecido como un producto ...

La asignatura tiene como objetivo la gestión del patrimonio arqueológico para ser ofrecido como un producto turístico, pero con una visión de manejo y conservación del recurso como un bien no renovable. La presente ...

Subjects / keywords: Big data; Computer science; Electronic books

Subjects / keywords: Computer algorithms; Databases; Data structures (Computer science); Structured programming

Subjects / keywords: Social sciences; Data processing; Statistics; Electronic books

Subjects / keywords: Programming languages (Electronic computers); R (Computer program language); Social sciences; Data processing; Electronic books

Subjects / keywords: Ecology; Data processing; Environmental sciences; R (Computer program language)

Subjects / keywords: Natural language processing (Computer science); Sentiment analysis; Public opinion; Data processing; Electronic books

Subjects / keywords: Data encryption (Computer science); Cryptography; Data processing; Computer security; Python (Computer program language); Electronic books