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Statistical Genomics

This volume expands on statistical analysis of genomic data by discussing cross-cutting groundwork material, public data repositories;

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Genomics in the Cloud Using Docker, GATK, and WDL in Terra

community. How do you adapt analysis tools and protocols to access and analyze that volume of data in the cloud? With this practical book;

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Computational Genomics with R

Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners;

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Computational Genomics with R

Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners;

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Topological Data Analysis for Genomics and Evolution

numbers, which are typically easier to work with. Topological data analysis is a rapidly developing subfield that leverages the tools of algebraic;

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Computational Genomics

prediction, mircroarray data analysis, and proteomics. The book is also useful as a teaching reference for graduates and undergraduate students.;

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Data Analysis and Visualization in Genomics and Proteomics

Data Analysis and Visualization in Genomics and Proteomics is the first book addressing integrative data analysis and visualization in this;

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Population Genomics with R

of multivariate methods, and advice on how to handle GIS data. The analysis of natural selection, a traditional issue in evolutionary biology, has known a;

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Population Genomics with R

Though the book's main focus is on data analysis, it will also treat other aspects linked to population genomics, including theory (Chap. 1;

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Data Production and Analysis in Population Genomics

that of the analysis methods. Therefore, Data Production and Analysis in Population Genomics purposely puts emphasis on protocols and methods;

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Data Production and Analysis in Population Genomics

that of the analysis methods. Therefore, Data Production and Analysis in Population Genomics purposely puts emphasis on protocols and methods;

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Data Mining and Applications in Genomics

Data Mining and Applications in Genomics contains the data mining algorithms and their applications in genomics, with frontier case studies;

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Data Mining and Applications in Genomics

Data Mining and Applications in Genomics contains the data mining algorithms and their applications in genomics, with frontier case studies;

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Genomics Data Analysis

discovery rates, preparing them to analyze their own genomics data and to critically evaluate published genomics research. Key Features;

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Genomics Data Analysis

discovery rates, preparing them to analyze their own genomics data and to critically evaluate published genomics research. Key Features: * dice;

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Meta-analysis and Combining Information in Genetics and Genomics

Novel Techniques for Analyzing and Combining Data from Modern Biological Studies Broadens the Traditional Definition of Meta-Analysis With;

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Meta-analysis and Combining Information in Genetics and Genomics

Novel Techniques for Analyzing and Combining Data from Modern Biological Studies Broadens the Traditional Definition of Meta-Analysis;

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Genomics and Proteomics Engineering in Medicine and Biology

-proteomics areas. Structures and algorithms are used to analyze genomic data and develop computational solutions for pathological understanding;

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Bioinformatics and Data Analysis in Microbiology

The rapid advancement of sequencing techniques, coupled with the new methodologies of bioinformatics to handle large-scale data analysis;

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Applied Genomics and Public Health

such as pharmacogenomics, genethics, big data, data translation and analysis, economic evaluation, genomic awareness and education, sociology;

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Bioinformatics and Biomedical Engineering

; bioinformatics for healthcare and diseases; biomedical engineering; biomedical image analysis; biomedical signal analysis; biomedicine; challenges;

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Bioinformatics and Biomedical Engineering

; bioinformatics for healthcare and diseases; biomedical engineering; biomedical image analysis; biomedical signal analysis; biomedicine; challenges;

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Advances in Bioinformatics and Computational Biology

, including sequence analysis; motifs, and pattern matching; biological databases, data management, data integration, and data mining; biomedical text;

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Bioinformatics and Biomedical Engineering

: bioinformatics tools and medical applications; omics data acquisition, processing, and analysis; bioinformatics approaches for analyzing cancer;

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High-dimensional Data Analysis

Over the last few years, significant developments have been taking place in high-dimensional data analysis, driven primarily by a wide;

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Plant Genome: Biodiversity and Evolution, Vol. 1, Part E

, congruence of karyotype and molecular data in Festuca and analysis of putative ancestors in Avena. The volume will be of interest to all students;

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Microarrays for an Integrative Genomics

experiments, the book discusses the foundations for analyzing microarray data sets, genomic data-mining, the creation of standardized nomenclature and;

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