Register training material
17 materials found

Authors: David Wishart  or Boris Steipe 


Informatics and Statistics for Metabolomics 2018 Module 6-Future of Metabolomics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 6-Future of Metabolomics http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-6-future-of-metabolomics Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases. Researchers Post-Doctoral Fellows Graduate students Biologists, Genomicists, Computer Scientists
Informatics and Statistics for Metabolomics 2018 Module 3-Databases for Chemical, Spectral, and Biological Data

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 3-Databases for Chemical, Spectral, and Biological Data http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-3-databases-for-chemical-spectral-and-biological-data Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases. Researchers Post-Doctoral Fellows Graduate Students Biologists, Genomicists, Computer Scientists
Informatics and Statistics for Metabolomics 2018 Module 2-Metabolite Identification and Annotation

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 2-Metabolite Identification and Annotation http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-2-metabolite-identification-and-annotation Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases. Researchers Graduate students Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists
Informatics and Statistics for Metabolomics 2018 Module 1-Introduction to Metabolomics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 1-Introduction to Metabolomics http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-1-introduction-to-metabolomics Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases. Researchers Graduate Students Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists
Exploratory Analysis of Biological Data using R 2018

Course covered for this workshop are broadly relevant for many areas of modern, quantitative biology such as flow cytometry, expression profile analysis, function prediction and more.

Exploratory Analysis of Biological Data using R 2018 http://tess.elixir-uk.org/materials/exploratory-analysis-of-biological-data-using-r-2018 Course covered for this workshop are broadly relevant for many areas of modern, quantitative biology such as flow cytometry, expression profile analysis, function prediction and more. Researchers Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists Graduate students
Introduction to R 2018

Course introduces essential ideas and tools of R, and covers statistical tests in R.

Introduction to R 2018 http://tess.elixir-uk.org/materials/introduction-to-r-2018 Course introduces essential ideas and tools of R, and covers statistical tests in R. Researchers Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists Graduate students
Exploratory Analysis of Biological Data using R 2017 Module 5-Hypothesis Testing

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Exploratory Analysis of Biological Data using R 2017 Module 5-Hypothesis Testing http://tess.elixir-uk.org/materials/exploratory-analysis-of-biological-data-using-r-2017-module-5-hypothesis-testing Course covers essential tools and strategies that are available for EDA through the free statistical workbench R. Researchers Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists Graduate Students
Exploratory Analysis of Biological Data using R 2017 Module 4-Clustering

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Exploratory Analysis of Biological Data using R 2017 Module 4-Clustering http://tess.elixir-uk.org/materials/exploratory-analysis-of-biological-data-using-r-2017-module-4-clustering Course covers essential tools and strategies that are available for EDA through the free statistical workbench R. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Exploratory Analysis of Biological Data using R 2017 Module 3-Dimension Reduction

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Exploratory Analysis of Biological Data using R 2017 Module 3-Dimension Reduction http://tess.elixir-uk.org/materials/exploratory-analysis-of-biological-data-using-r-2017-module-3-dimension-reduction Course covers essential tools and strategies that are available for EDA through the free statistical workbench R. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Exploratory Analysis of Biological Data using R 2017 Module 2-Regression

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Exploratory Analysis of Biological Data using R 2017 Module 2-Regression http://tess.elixir-uk.org/materials/exploratory-analysis-of-biological-data-using-r-2017-module-2-regression Course covers essential tools and strategies that are available for EDA through the free statistical workbench R. Researchers Graduate Students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Exploratory Analysis of Biological Data using R 2017 Module 1-Exploratory Data Analysis

Course covers essential tools and strategies that are available for EDA through the free statistical workbench R.

Exploratory Analysis of Biological Data using R 2017 Module 1-Exploratory Data Analysis http://tess.elixir-uk.org/materials/exploratory-analysis-of-biological-data-using-r-2017-module-1-exploratory-data-analysis Course covers essential tools and strategies that are available for EDA through the free statistical workbench R. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Introduction to R 2017

Course covers the bioinformatics tools available for meeting the challenges of data handling and breaking down problems into structured parts using R.

Introduction to R 2017 http://tess.elixir-uk.org/materials/introduction-to-r-2017 Course covers the bioinformatics tools available for meeting the challenges of data handling and breaking down problems into structured parts using R. Researchers Graduate Students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Informatics and Statistics for Metabolomics 2017 Module 6-Future of Metabolomics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 6-Future of Metabolomics http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-6-future-of-metabolomics Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Informatics and Statistics for Metabolomics 2017 Module 5-MetaboAnalyst

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 5-MetaboAnalyst http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-5-metaboanalyst Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases. Researchers Graduate Students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Informatics and Statistics for Metabolomics 2017 Module 3-Databases for Chemical, Spectral, and Biological Data

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 3-Databases for Chemical, Spectral, and Biological Data http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-3-databases-for-chemical-spectral-and-biological-data Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases. Researchers Graduate Students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Informatics and Statistics for Metabolomics 2017 Module 2-Metabolite Identification and Annotation

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 2-Metabolite Identification and Annotation http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-2-metabolite-identification-and-annotation Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases. Researchers Graduate students Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists
Informatics and Statistics for Metabolomics 2017 Module 1-Introduction to Metabolomics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 1-Introduction to Metabolomics http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-1-introduction-to-metabolomics Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows